bluuebunny/crossref_metadata_2025_split huggingface dataset:
ADPrep ‐ A fully automated Alzheimer’s Disease Neuroimaging Preprocessing Pipeline for MRI and multi‐tracer PET data
Authors: Dehsarvi Amir , Denecke Jannis , Biel Davina , Dewenter Anna , Roemer Sebastian Niclas , Steward Anna , Wanger Fabian , Brendel Matthias , Franzmeier Nicolai 
Published: December 2023

AbstractBackgroundState‐of‐the‐art preprocessing of MRI and PET data is crucial for Alzheimer’s disease (AD) neuroimaging research. Therefore, standardization and harmonization of neuroimaging preprocessing across sites is key to generate comparable and sharable datasets and to reduce potential bias introduced by different preprocessing strategies. Further, neuroimaging preprocessing requires strong expertise in different programming languages (R/MATLAB/Python/Bash) and software packages (SPM/FSL/AFNI/FreeSurfer), i.e., a major barrier for non‐expert users. Therefore, we developed a docker‐based, state‐of‐the‐art, fully automated, neuroimaging toolbox that integrates robust preprocessing of structural/functional MRI, and multi‐tracer PET (amyloid/tau/FDG/TSPO), generating easy to use spreadsheet and nifti outputs. The toolbox requires no programming expertise and can facilitate neuroimaging analyses, data harmonization and sharing across the AD neuroimaging community.MethodsThe pipeline works on standardized bids‐formatted data and was fully developed in nipype (see Figure 1). Preprocessing for structural MRI includes volumetric and cortical thickness assessments for widely used brain atlases (Desikan‐Killiany/Schaefer/LPBA/Hammers/Neuromorphometrics/Cobra/Destrieux), plus spatially normalized and smoothed grey/white‐matter segments for voxel‐based morphometry and generation of subject‐specific PET‐reference regions. Functional MRI processing includes slice‐timing and motion correction, nuisance regression, spatial normalization, and functional connectivity assessments for the above‐mentioned atlases. PET processing includes generation of spatially normalized SUVR images for different tracer‐specific reference regions, as well as extraction of atlas‐based SUVRs (PVE and non‐PVE‐corrected). Standardized imaging outputs in FreeSurfer space were benchmarked against available ADNI data to illustrate comparability with existing pipelines (see Figure 2). Cluster implementation is provided to ensure large‐scale data processing.ResultsThe toolbox was tested successfully on large‐scale multimodal datasets, including several thousand scans from ADNI, ADNI‐DOD, and A4 with an overall processing failure rate of <4%. Using ADNI data as a benchmark, our data closely reproduce global amyloid‐PET (r = 0.99, p<0.001, Fig.2A) and temporal meta tau‐PET SUVRs (r = 0.98, p<0.001, Fig.2B), suggesting that PET‐thresholds can be applied. Runtime is ∼1h for a structural MRI and ∼5hrs for a PET including PVE‐correction.ConclusionsWe propose a user‐friendly multimodal robust neuroimaging preprocessing toolbox, that can be applied to different neuroimaging datasets by non‐expert users. The toolbox provides outputs that can be directly used for statistical analyses. Future work involves implementing other imaging modalities, e.g., diffusion tensor imaging.
Gotcha! A trial of an app‐based therapy for proper name anomia in people with dementia
Authors: Badalova Aygun 
Published: December 2023

AbstractObjectivesProper name anomia is a common experience that can become amplified in patients with a diagnosis of dementia (PWD). The Gotcha! app aims to provide practice‐based therapy for PWD to relearn the names of key people in their lives. It has been developed according to the principles of errorless learning, which have previously been shown to improve the remembering the familiar people’s names and benefit the relationship between the PWD and their loved ones. (Clare et al, 1999, 2000, 2003).MethodsGotcha! is a digital confrontation naming therapy app which enables patients to train one face per day by using photos that the app represents. During the development phase we carried our qualitative research (thematic analysis) on why PWD get involved in research projects such as ours. Gotcha! therapy block lasts for six weeks and prior to the therapy patients complete a multiple baseline paradigm with eight weekly tests of free naming of the to‐be trained faces. During the therapy, a novel speech verifier is used to provide real‐time feedback (Barbera et al. 2020). Two analyses method is used to investigate the behavioural data: 1) within‐subject non‐parametric analysis using Tau‐U metric (Parker et al. 2011); 2) a parametric group analysis using an ANOVA.ResultsThe thematic analysis revealed four themes that will be discussed in more detail on the talk.In terms of the quantitative data, our results from the first 16 subjects showed: 1) Tau‐U. 73% showed a positive trend with better naming during the training phase with 5/10 reaching statistical significance. 2) ANOVA demonstrated a significant effect at the group level of training>baseline phase, F(1,9) = 6.68, p = .029.
GABA transporters gene expression associates with [18F]FDG‐PET signal in regions typically hypometabolic in Alzheimer’s disease
Authors: Carello‐Collar Giovanna , Ferrari‐Souza João Pedro , Machado Luiza Santos , Povala Guilherme , Limberger Christian , Pascoal Tharick A. , Zimmer Eduardo R 
Published: December 2023

AbstractBackgroundIt is suggested that the [18F]fluorodeoxyglucose(FDG)‐PET signal reflects astrocyte and neuronal activity, with the excitatory glutamate uptake by astrocytes as the trigger for brain glucose metabolism. The inhibitory neurotransmitter γ‐aminobutyric acid (GABA) is taken up by neurons and astrocytes through the GABA transporters (GAT) 1 and 3. However, its role in the [18F]FDG‐PET signal in healthy aging and Alzheimer’s disease (AD) remains poorly investigated. Thus, we aimed to explore associations between neuronal and astrocytic GABA transporters gene expression with [18F]FDG‐PET in cognitively unimpaired (CU) and AD individuals.MethodWe obtained [18F]FDG‐PET imaging data of CU and AD from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) (Table 1). GAT1 and GAT3 gene expression in the brain was obtained from the Allen Brain Atlas (Table 1, Figure 1). We extracted SUVr (pons as reference region) and mRNA values using the RMINC package and performed Pearson’s correlation to test the association between [18F]FDG‐PET and GABA transporters mRNA (p‐value < 0.05).ResultIn brain regions typically hypometabolic in AD, we observed a strong positive association of [18F]FDG‐PET SUVr with GAT1 and GAT3 gene expression in CU (GAT1: r = 0.93; p < 0.0001; Figure 2A, GAT3: r = 0.94; p < 0.0001; Figure 2B) and AD individuals (GAT1: r = 0.9; p < 0.0001; Figure 2A, GAT3: r = 0.92; p < 0.0001; Figure 2B). By contrast, in brain regions typically resilient, we found a weak correlation with CU individuals (GAT1: r = 0.32; p = 0.016; Figure 2C, GAT3: r = 0.26; p = 0.04; Figure 2D) and no significant correlation in AD patients (GAT1: r = 0.24; p = 0.07; Figure 2C, GAT3: r = 0.24; p = 0.059; Figure 2D).ConclusionOur results demonstrate a significant strong positive association between [18F]FDG‐PET SUVr and GABA transporters gene expression in CU and AD in hypometabolic regions. These findings suggest that GABA transporters are involved with brain glucose metabolism in regions classically vulnerable to AD pathology.
A portable eye tracking experiment for the assessment of cognitive impairment in presymptomatic frontotemporal dementia
Authors: Convery Rhian S , Goldsmith Sophie E , Nicholas Jennifer M , Kaski Diego , Rohrer Jonathan D. , Russell Lucy L. 
Published: December 2023

AbstractBackgroundEye tracking can be useful for measuring cognitive function in frontotemporal dementia (FTD), as the tasks do not require behavioural or verbal responses. However, most systems are highly expensive and require experiments to be conducted in artificial environments. We developed a fully portable eye tracking protocol using the Tobii Pro Nano, a small, low‐cost eye tracker. The aim was to investigate if the portable experiment can detect presymptomatic impairment in FTD using instructionless tasks of social cognition.MethodParticipants were recruited from the Genetic FTD Initiative (GENFI), including 41 mutation carriers (mean age = 43.0, standard deviation (SD) = 11.0), and 14 non‐carriers (mean age = 40.4, SD = 7.14). Participants completed tasks of simple and complex emotion recognition that involved viewing four images (one target face (simple) or pair of eyes (complex) and three non‐target) followed by a target emotion word and then the original four images alongside the emotion word. A dwell time change score was calculated by subtracting the percentage dwell time for the target image before the word appeared from the percentage dwell time after the word appeared. A lower dwell time change score signifies impaired performance. Linear mixed effects models were used to compare performance on each of the tests, with the dwell time change score included as the variable of interest and age, target type (target, non‐target), and genetic status (carrier, non‐carrier) included in the model as fixed effects.ResultThe average (standard deviation) mean percentage dwell time change score in the target image was lower at 52.2% (15.8) for the mutation carriers compared with 56.5% (7.01) for non‐carriers on the simple emotion task (p = 0.006), and 23.4% (11.2) for carriers compared with 27.3% (7.46) for non‐carriers on the complex emotion task (p = 0.076).ConclusionThese eye tracking tasks may be a useful tool for assessing deficits in social cognition in presymptomatic FTD, something that has been difficult to measure with pen and paper neuropsychometry. Therefore, this portable eye tracking experiment has the potential to be a low‐cost biomarker for monitoring the progression of FTD in clinical trials, both at home and in the clinic.
Cholinesterase inhibitors are associated with large reductions in hospitalization for cardiovascular events and mortality in patients with Alzheimer’s dementia and heart failure
Authors: Wessberg Marianne Reimers , Xu Hong , Fastbom Johan , Seiger Ake , Eriksdotter Maria 
Published: December 2023

AbstractIntroductionCholinesterase inhibitors (ChEIs) are approved for treatment of Alzheimer’s dementia (AD). ChEIs inhibit the enzyme acetylcholinesterase, increasing the duration of action of acetylcholine in the central and peripheral nervous systems. ChEIs are known to be anti‐inflammatory and to have negative chronotropic effects. Observational studies by us and other groups have indeed shown an association with use of ChEIs in AD with lower risk of death and cardiovascular events (CVD) including myocardial infarction, heart failure (HF), and stroke. We next wanted to investigate whether ChEI treatment in AD patients with HF is associated with reduced risk for mortality and for hospitalization due to CVD.MethodsData from the Swedish registry for dementia disorders, SveDem,was linked to the Patient‐, Prescribed Drug‐ and Cause of death registries. In a propensity score (PS) matched cohort of patients with AD and HF, the association between ChEI use and all‐cause death or hospitalization due to CVD was examined with Cox proportional hazards models.ResultsThe PS matched cohort included 455 patients with HF prior to the AD diagnosis with ChEI and 455 non‐ChEI users. During a median follow‐up time of 2.14 years, 549 deaths occurred. Compared to non‐users, ChEI use was associated with 21% lower risk of death (adjusted HR 0.79; 0.66‐0.96). Galantamine and donepezil (0.64; CI 0.47‐0.87 and 0.80; CI 0.64‐0.98) but not rivastigmine (0.96; CI 0.73‐1.28) were associated with lower risk of death. Any ChEI use was associated with a 47% (CI 0.38‐0.75) reduction in risk of hospitalization due to HF and a 52% reduction (CI 0.32‐072) among donepezil‐users.ConclusionsThis study supports previous reports that treatment with ChEIs in AD is associated with reduced mortality risk. We here show that this association is also found in patients with HF and AD but with differential effects among the ChEIs. Further studies are needed to elucidate the mechanisms. The study also showed a substantial reduction in hospitalization due to CVD. Our results highlight the impact of cardiovascular comorbidities in AD which need to be considered in clinical trials as would the impact of the baseline treatment with ChEIs in new anti‐dementia drug trials.
Exploring the Causal Association between Brain Iron Accumulation and Alzheimer’s Disease: A Two‐Sample Univariable Mendelian Randomisation Analysis
Authors: Zagos Loukas , Elliott Paul , Tzoulaki Ioanna , Dehghan Abbas 
Published: December 2023

AbstractBackgroundAlzheimer’s disease aetiology is complex and not fully understood. Brain iron has been increasingly implicated in the pathology of neurodegenerative diseases, and a myriad of epidemiological studies has supported a connection between brain iron accumulation and Alzheimer’s disease, but evidence remains inconsistent. Additionally, genetic studies have suggested that variations in genes that regulate brain iron metabolism may increase the risk of developing Alzheimer’s disease.MethodIn this study we conduct two‐sample univariable Mendelian randomisation analysis, leveraging the largest available summary statistic genetic data from genome‐wide associations studies on quantitative susceptibility mapping phenotypes to explore potentially causal associations between iron deposition measured in 18 brain structures and Alzheimer’s disease.ResultWe identified that higher genetically predicted brain iron accumulation in left putamen was associated with higher odds of Alzheimer’s disease (Odds ratio (OR) per standard deviation (SD) higher genetically predicted median susceptibility: 1.11, 95% confidence interval (CI): 1.03 to 1.20) and higher genetically predicted brain iron accumulation in right putamen was also associated with higher odds of Alzheimer’s disease (OR: 1.10, 95% CI: 1.01 to 1.20). However, genetic predisposition to higher Alzheimer’s disease liability was associated with lower brain iron deposition in right thalamus (beta per unit higher log‐odds of Alzheimer’s disease: ‐0.04, 95% CI: ‐0.08 to ‐0.01), left amygdala (beta: ‐0.04, 95% CI: ‐0.07 to ‐0.01), right amygdala (beta: ‐0.04, 95% CI: ‐0.07 to ‐0.01), left thalamus (beta: ‐0.03, 95% CI: ‐0.07 to ‐0.003) and left putamen (beta: ‐0.04, 95% CI: ‐0.08 to ‐0.002).ConclusionThis work provides a new layer of evidence using genetic association data that supports a potentially causal effect of iron accumulation in putamen on Alzheimer’s disease, which has been proposed in the literature. Iron can promote oxidative stress, which can contribute to neuronal damage and death in the putamen. Additionally, iron can disrupt the normal functioning of the basal ganglia, which in turn may lead to movement disorders, a symptom observed in Alzheimer’s disease. Therefore, despite the lack of evidence from clinical trials, iron‐targeted therapeutic strategies could be a beneficial approach for contributing to the treatment of Alzheimer’s disease.
Monitoring Daytime Napping in Community Dwelling Older Adults Using Contactless Sleep Technologies
Authors: Ravindran Kiran K.G. , Monica Ciro Della , Atzori Giuseppe , Lambert Damion , Revell Victoria Louise , Dijk Derk‐Jan 
Published: December 2023

AbstractBackgroundIncreased daytime napping and excessive sleepiness are associated with cognitive decline in older adults, especially in people living with dementia (PLWD) [1]. Subjective assessments of naps are burdensome and maybe unreliable in PLWD and hence there is a need for technologies that provide objective longitudinal assessment of the incidence and duration of naps. Here we compare two contactless sleep technologies (CSTs) against sleep diary and actigraphy for monitoring daytime napping in community dwelling non‐demented older adults.MethodTwo under‐mattress CSTs (Withings Sleep Analyser [WSA] and Emfit QS [Emfit]) along with actigraphy (Actiwatch Spectrum [AWS]) were deployed in the home of 17 older adults for a period of 14 days (≥65 years; Mean Age ± SD = 72 ± 4.49; 6 Women). The ground truth nap information was collected using an extended consensus sleep diary that included additional information about naps (timing, duration, and location). We analyzed the agreement of the napping events and duration estimated by WSA, Emfit and AWS against the sleep diary reported events.ResultThe CSTs only detected in‐bed naps whilst the AWS detected both in‐bed and not‐in‐bed naps. Although all the compared devices detected spurious naps unreported in the sleep diary, it was highest in AWS (81% of total naps detected) followed by Emfit (63%) and WSA (16%) as shown in Figure 1. Among the CSTs, WSA accurately detected more in bed naps while registering less spurious naps compared to Emfit but had lower duration agreement to sleep diary (Figure 2). Further, when the contribution of daytime naps to 24‐h total sleep time was computed, the WSA estimate (12.8±6.1%) was closest to the sleep diary estimate (12.9±9.1%) followed by AWS (15.6±9.9%) and Emfit (17.2±11.1%).ConclusionCSTs, with their ability to provide both contextual location information and objective measures of napping, such as timing and duration, offer a reliable and unobtrusive alternative to traditional methods such as sleep diary and actigraphy for long‐term round‐the‐clock monitoring of sleep in older adults.References:[1] Li, P, Gao, L, Yu, L, et al. Daytime napping, and Alzheimer’s dementia: A potential bidirectional relationship. Alzheimer’s Dement. 2023; 19: 158– 168. https://doi.org/10.1002/alz.12636
LANGaware: biomarker workflows for classifying neurodegenerative and affective disorders across languages and severity levels
Authors: Rentoumi Vassiliki , Vassiliou Evangelos , Pittaras Nikiforos , Demiraj Admir , Paliouras George , Sali Dimitra 
Published: December 2023

AbstractBackgroundA wide range of neurodegenerative disorders impair communication faculties, manifested as subtle changes in speech and language. Following trends in Machine Learning (ML), Text and Multimedia Analysis, recent works pursue classification of such disorders by developing biomarkers useful for cognitive status description. However, investigations that gauge biomarker applicability on cases of radically different impairment / symptom severity have been under‐investigated. In this work, we build upon previous research and evaluate LANGaware’s biomarker suite in the drastically different tasks of Dementia and Depression classification. For both cases, we use appropriate Healthy Controls and evaluate the proposed biomarker workflow under a multi‐language experimental investigation.MethodWe utilize audio recordings and transcripts from patient responses to verbal cognitive assessment tasks. These are analyzed with LANGaware’s multimodal biomarker pool, mapping raw data to biomarkers scores that quantify vocal, linguistic and grammatical usage proficiency, structure and patterns, by applying both statistical analysis and explainable template matching. Biomarkers activations are fed to ML workflows composed of gradient boosting learners that employ feature selection, filtering and ensemble‐based learning to arrive at configurations best suited for discriminating the disorder of interest. The pipeline is evaluated using a standard train‐test and cross‐validation setup.ResultExperimental results indicate that our method achieves weighted F1 test scores of 82.49% for Greek Dementia classification, using a train / test dataset of 1271 / 624 instances and 80.28% on 570 / 243 English data. We use the same pipeline and biomarker pool for Depression classification, reaching 74.03% and 71.36% performance scores, obtained from 73 / 31 and 652 / 42 available train‐test data, for Greek and English respectively.ConclusionThe above findings show that the proposed biomarker pool generalizes across neurodegenerative and affective disorders of radically different severity. As a result, they constitute valuable decision support tools for accurate, automatic and explainable early diagnosis, facilitating proactive care, improved symptom management and better patient quality of life. Future research efforts include extending our experimental evaluation of LANGaware biomarkers to additional disorders and diseases, as well as expanding the biomarker set to enable analysis of additional modalities.
Blood‐based biomarkers for clinical trials of Alzheimer’s disease in Down syndrome
Authors: Ashton Nicholas J. , Montoliu‐Gaya Laia , Alcolea Daniel , Huber Hanna , Blennow Kaj , Jeromin Andreas , Fortea Juan , Zetterberg Henrik 
Published: December 2023

AbstractBackgroundA blood biomarker for a clinical diagnosis of Alzheimer’s disease (AD) is of particular importance in Down syndrome, where a change in cognitive function is often difficult to delineate. Recent advances in ultra‐sensitive detection methods have allowed for the quantification of GFAP, p‐tau and NfL, which demonstrate high specificity for diagnosis of AD pathology and neurodegeneration, which has been utilised in recent anti‐amyloid trials.MethodsNovel data presented in this talk will compare a multi‐centre study (n>800) on plasma NfL, GFAP, and phosphorylated tau (p‐tau181, p‐tau217, p‐tau231) from sporadic AD, familial AD, adults with Down syndrome and euploid controls in a cross‐sectional and longitudinal manner.ResultsWe compared plasma biomarker performance to monitor clinical progression or identify changes in 18F‐fluorodeoxyglucose, amyloid PET and cortical atrophy by MRI. Further, explorative proteomics in cerebrospinal fluid (CSF) aims to identify novel candidates of clinical decline in Down syndrome individuals. Lastly, novel pilot data demonstrate that measures of GFAP, NfL and p‐tau are possible via capillary blood, extracted from a finger prick test, which have important implications as an off‐site blood collection in the Down Syndrome community without the need for strict blood processing protocols.ConclusionPlasma biomarkers of sporadic AD, specifically GFAP, NfL and p‐tau217, have equally high performance to AD pathology in Down Syndrome individuals with possible applications in clinical practice and clinical trials. Moreover, GFAP and NfL may act as important biomarkers in an off‐site finger prick collection which will increase inclusion and easier monitoring in the Down Syndrome community.