bluuebunny/crossref_metadata_2025_split huggingface dataset:
Detecting amyloid positivity from MRI scans using comprehensible convolutional neural networks
Authors: Levin Fedor , Li Qingyue , Singh Devesh , Buerger Katharina , Fliessbach Klaus , Heneka Michael T. , Kleineidam Luca , Laske Christoph , Perneczky Robert , Peters Oliver , Priller Josef , Ramirez Alfredo , Schneider Anja , Spottke Annika , Wagner Michael , Wiltfang Jens , Düzel Emrah , Jessen Frank , Teipel Stefan , Dyrba Martin 
Published: January 2025

AbstractBackgroundAnalysis of neuroimaging data based on convolutional neural networks (CNNs) can improve detection of clinically relevant characteristics of patients with Alzheimer’s disease (AD). Previously, our group developed a CNN‐based approach for detecting AD via magnetic resonance imaging (MRI) scans and for identifying features that are relevant to the decision of the network. In the current study, we aimed to evaluate the potential utility of applying this approach to MRI scans to assist in the identification of individuals at high risk for amyloid positivity to aid in the selection of study samples and case finding for treatment.MethodIn the current analysis, we have trained a CNN to detect amyloid positivity using MRI scans from 1461 Alzheimer’s Disease Neuroimaging Initiative (ADNI) participants (498 cognitively normal participants, 103 participants with significant memory concern, 640 participants with mild cognitive impairment, and 220 participants with AD dementia). Amyloid positivity was assessed via amyloid PET scans obtained with [18F]florbetapir or [18F]florbetaben and quantified on a Centiloid scale. A threshold of 24.1 CL categorized 46% of participants as amyloid‐positive. The modeling approach was evaluated using 10‐fold cross‐validation, the number of epochs in training was set to 10.ResultFor each of 10 cross‐validation folds, we selected a model state corresponding to an epoch showing best performance in the validation partition. Balanced accuracy across these models ranged from 0.62 to 0.72 with an average of 0.68 (SD = 0.03).ConclusionWe used a previously established approach to train CNNs for detecting amyloid positivity using MRI scans. Such models, particularly when tuned to have low rates of false negatives, have a potential to enhance identification of patients who would benefit from more in‐depth assessments, which could then inform antibody treatment. We are conducting ongoing work to improve and characterize the modeling approach, including evaluation of relevance maps which indicate importance of brain regions for detecting amyloid positivity. Future work will evaluate the role of amyloid positivity threshold selection. Planned analyses also include validation in independent data such as the German DZNE ‐ Longitudinal Cognitive Impairment and Dementia Study (DELCODE) dataset.
Exposure Severity and Cognitive Dysfunction are Mediated by Low‐Grade Cerebral Amyloidosis: A PET/MRI study of World Trade Center responders
Authors: Kritikos Minos , Zhou Juin W. , Huang Chuan , Vaska Paul , Clouston Sean A.P. , Luft Benjamin J 
Published: January 2025

AbstractBackgroundWorld Trade Center (WTC) responders endured exposures to neurotoxic dust particulate matter. This neuroimaging study examined the presence of amyloidosis in Alzheimer’s disease (AD) regions of interest (ROIs) and associations with exposure duration.MethodSimultaneous positron‐emission tomography with [18F]‐florbetaben and magnetic resonance neuroimaging was acquired on 34 middle aged WTC responders. Centiloid scale used mean standardized uptake value ratio (SUVR) with between subjects comparisons of cognitively unimpaired (n = 17) and early‐onset dementia (n = 17) responders. Pathway analyses investigated potential neuropathological cascades.ResultOnly one subject was Centiloid positive. However, considerable SUVRs in non‐AD ROIs associated with changes in cortical mean diffusivity, cortical thickness, cognition, and exposure duration, mediated by the olfactory bulb.ConclusionFibrillar amyloidosis may have originated in, and spread from the olfactory cortex because of prolonged exposures to WTC neurotoxic dust. Our study also identifies a non‐AD neuropathological topology of amyloidosis, which associated with lower measures of brain health.
Relationship of Mito‐Nuclear Genetics to FDG‐PET Alzheimer’s Disease Biomarkers in Aging
Authors: Honea Robyn A , Vidoni Eric D , Lepping Rebecca J , Morris Jill K , Wilkins Heather M , Burns Jeffrey M , Swerdlow Russell H 
Published: January 2025

AbstractBackgroundA growing amount of data has implicated the various roles of nuclear genes involved in mitochondrial function, and mitochondrial genes, on risk for Alzheimer’s disease (AD) and AD neuroimaging biomarkers. To date, no studies have investigated the relationship of mitochondrial haplogroups or the APOE and TOMM40 genes on brain glucose metabolism, a sensitive early marker of metabolic decline and possible mitochondrial dysfunction in AD.MethodWe analyzed regional standard uptake value ratio (SUVR) differences in 18F‐fluorodeoxyglucose positron emission tomography (FDG‐PET) using SPM12 and CAT12 software between nondemented (ND, n = 69), mild cognitively impaired (MCI, n = 19) and AD (n = 18) groups in a sample of individuals from the University of Kansas Alzheimer’s Disease Research Center Cohort, controlling for age, sex, and education. We then tested whether genetic variation in APOE (e4‐carriers vs. non‐carriers), TOMM40 rs2075650 (‘650 G‐allele carriers vs. A‐Allele) or mitochondrial haplogroup significantly influenced regional differences in glucose metabolism in nondemented individuals, as they made up the bulk of our sample of individuals with these scans.ResultWe found that, as expected, individuals with AD had significantly decreased glucose metabolism across all regions except the motor cortex and the cerebellum compared to ND individuals (Figure 1). Our results across various gene groups, controlling for age, sex, education, and with and without APOE e4 showed that there were no significant differences in FDG‐PET SUVR between ND TOMM40 ‘650 G‐allele carriers, or mitochondrial haplogroups (H, JT, and UK groups combined), however APOE e4‐carriers had significantly lower glucose metabolism in the anterior cingulate, superior medial frontal, posterior cingulate, medial frontal, right middle frontal, and bilateral superior frontal cortices than e4‐non carriers (Figure 2). There were no significant effects of APOE e4 on glucose metabolism in limbic regions.ConclusionThe APOE e4 allele may have more impact on FDG‐PET in default mode regions (posterior and anterior cingulate, medial frontal cortex) than TOMM40 '650, a larger study in cognitively healthy individuals will be needed to confirm these results.
Lower slow wave sleep and rapid eye‐movement sleep are associated with brain atrophy of AD‐vulnerable regions
Authors: Cho Gawon , Mecca Adam P , Buxton Orfeu M. , Liu Xiao , Miner Brienne 
Published: January 2025

AbstractBackgroundSleep deficiency is associated with an increased risk of Alzheimer’s disease (AD), warranting research on underlying mechanisms. This study examined the association of sleep architecture with anatomical features frequently observed in AD: (1) atrophy of cuneus, hippocampus, entorhinal, inferior parietal, parahippocampal, and precuneus regions (henceforth referred to as “AD‐vulnerable regions”) and (2) the presence of cerebral microbleeds.MethodIn 271 participants of the Atherosclerosis Risk in the Communities Study, we examined the prospective association of baseline sleep architecture with anatomical features of the brain identified on MRI conducted ∼17 years later. Sleep architecture was quantified as the proportion of time spent in slow wave sleep (SWS), proportion of time spent in rapid eye‐movement sleep (REM), and the number of arousals per hour of total sleep time using polysomnography. Outcomes included (1) volumetric measurements of each AD‐vulnerable region and (2) the presence of any cerebral microbleeds (CMBs) and that of lobar CMBs, which are more specifically associated with AD. We analyzed the association of each sleep predictor with each brain outcome, adjusting for demographics, baseline cognitive function, APOE genotype, intracranial volume, other covariates, and false discovery rate (FDR; family‐wise p<.05).ResultHaving less SWS was associated with smaller volumes of the inferior parietal region (β = ‐41.56 mm3 per percentage point (PP) [95%CI = ‐73.97, ‐9.15]) and cuneus (β = ‐11.56 mm3 per PP [‐20.51,‐2.62]) after adjustments for covariates. Having less REM was associated with smaller volumes of the inferior parietal region (β = ‐73.13 mm3 per PP [‐126.95, ‐19.30]) and precuneus (β = ‐32.46 mm3 per PP [‐64.48,‐0.44]). After FDR adjustments, lower SWS and REM, respectively, were associated with lower volumes of the inferior parietal region only. Arousal index was not associated with the volumes of AD‐vulnerable regions. None of the sleep architecture variables were associated with the presence of CMBs or lobar CMBs.ConclusionSleep deficiency is associated with the atrophy of the inferior parietal region, which is often observed in early AD. Sleep architecture may be a modifiable risk factor for AD pathogenesis.
Impact of Grey Matter Volume and White Matter Hyperintensities on Functional Capacity for Activities of Daily Living: A Study in the Alzheimer’s Disease Continuum
Authors: Campo Cecilia Gonzalez , Henriquez Fernando , Contreras Patricio Riquelme , Lillo Patricia , Martínez‐Pernía David , Thumala Daniela , Aboitiz Francisco , Chonchol Andrea Slachevsky , Henriquez Rodrigo 
Published: January 2025

AbstractBackgroundThe Alzheimer’s disease (AD) continuum is composed of the stages of Subjective Cognitive Decline (SCD), Mild Cognitive Impairment (MCI), and Alzheimer’s Disease Dementia (ADD). The decrease in gray matter volume (GMV) secondary to cortical atrophy, commonly seen in this continuum, is related to cognitive and activities of daily living (ADL) impairment. Additionally, White Matter Hyperintensities (WMH), MRI abnormalities frequently observed in older adults and patients with dementia, are also associated with cognitive and ADL performance. This study aimed to evaluate the relationship of GMV and WMH on ADL performance across the AD continuum.MethodWe conducted a cross‐sectional study of 77 SCD, 30 MCI, and 23 ADD subjects, matched for age, sex, and education. ADL was assessed using the Technology‐Activities of Daily Living Questionnaire (T‐ADLQ). Total GMV was calculated via voxel‐based morphometry analysis in SPM12. Total (tWMH), periventricular (pWMH), and subcortical (sWMH) WMH lesions were calculated with the lesion prediction algorithm (LST) and the ALVIN mask (Figure 1a). Spearman correlation analysis was used to test associations among GMV, WMH, and ADL. A linear regression model was employed to assess the relative effect of GMV and WMH on ADL scores.ResultADD patients performed worse on ADL and showed decreased GMV and higher pWMH burden in comparison with all the other AD continuum groups (Table 1). Within the whole sample, worse ADL scores correlated significantly with decreased GMV and higher pWMH load (Figure 1b and 1c, respectively). In addition, lower GMV was correlated with greater pWMH load (Figure 1d). The linear regression model (R2 = 0.183, F = 13.890, p = 0.000) showed that only GMV had a significant impact (Beta = ‐0.338, p = 0.000), while pWMH load did not significantly influence ADL performance (Beta = 0.164, p = 0.064).ConclusionLower GMV and higher pWMH load are associated with worse ADL performance. These features differentially contribute to explain ADL performance across the AD continuum, with a more pronounced effect of GMV over pWMH. Widespread GM atrophy and pWMH burden are distinctive features of ADD, strongly suggesting a fundamental detrimental role of these structural brain abnormalities along the AD continuum.
Comprehensive Multi‐Neuron Imaging During Aging and Degeneration in C. elegans
Authors: Yadav Dilip , Wirak Gregory , Connor Christopher , Gabel Chritopher 
Published: January 2025

AbstractBackgroundDespite the prevalence of Alzheimer’s Disease in the aged human population and advancements in our understanding of the disease at the molecular level, we still lack a fundamental understanding of how cognitive dysfunction stems from alterations in cellular neuron dynamics and how it relates to the normal aging process. To address this gap in knowledge, we measured the breakdown of nervous system function with cellular resolution during normal aging and in an Alzheimer’s Disease model.MethodEmploying comprehensive multi‐neuron florescence microscopy in the nematode worm, C. elegans, a simple yet powerful model animal, we can measure neuron activity across the majority of the animal’s nervous system with single cell resolution. To measure how system‐state dynamics and neuronal connectivity breakdown during normal aging and in the disease model, imaging was performed throughout the animal’s lifespan in wild‐type as well as a transgenic strain in which human amyloid‐ß (Aß) peptide (1‐42) is pan‐neuronally expressed.ResultsDuring normal aging we measure a breakdown in system‐state dynamics that accompany shifts in activity to higher frequencies and a global loss of inhibitory signaling. In Aß expressing animals this process is accelerated and includes loss of both inhibitory and excitatory signaling.ConclusionOur work is defining the functional degradation of a complete nervous system from single neurons to system‐wide dynamics during normal aging and in the disease model. In doing so we are revealing the specific changes in neuron activity at the cellular level that cause the breakdown of global nervous system dynamics. These results will enable a knowledge‐based approach to novel neurotherapeutic strategies in the treatment and prevention of dementia.
Mapping alterations in the hippocampal subfields in the ARTE10 mouse model of Alzheimer's disease using dMRI derived soma and neurite density maps
Authors: Shahid Syed Salman , Jarvis Erin E , Butch Elizabeth R , Snyder Scott E , Wu Yu‐Chien 
Published: January 2025

AbstractBackgroundThe hippocampus, a region vital for memory and cognition, is prone to abnormal deposition of beta‐amyloid (Aß) during the early stages of the Alzheimer’s disease. Aß‐associated pathophysiological mechanisms instigate dendritic deficit, neuronal loss, and neuroinflammation, leading to abnormal functional and behavioral changes. These factors directly impact tissue microstructures. Histological studies suggest subfield specific Aß accumulation. The aim of the current study is to map the changes in soma‐ and neurite‐density in the hippocampal‐subfields due to Aß load in the ARTE10 mouse‐model of AD using a compartment‐specific diffusion model.MethodTen‐month‐old male ARTE10 (N=8) and age‐matched littermate controls underwent MRI on a 9.4T scanner (Bruker BioSpin, GmbH, Germany) equipped with an 1H cryogenic surface coil. DWIs were acquired using a 2D multi‐shot spin‐echo echo planar imaging sequence using the following parameters: TE/TR=26/4000 ms; voxel size=125x125x400 µm3, 20 slices, 4 segments, b values= (500, 1000, 2500, 4000, 5500, 7000) s/mm2 and 5 b0 per b‐shell. The averaged b0 image was non‐linearly registered to Badhwar hippocampus atlas. The hippocampal‐subfields (CA1, CA2, CA3, CA4‐DG, subiculum, and stratum‐granulosum of hippocampus (SGH)) in atlas space were inverse transformed to diffusion space. Multi‐compartment microstructural estimation was performed using soma and neurite density imaging (SANDI) model. This model provided volume fractions for extra‐cellular (fec), intra‐neurite (fin), and intra‐soma (fsoma) compartments (Figure 1). The regional mean values of microstructural parameters of individual subfields were extracted and used in a general linear model for group comparisons.ResultThe group‐level differences (WT vs. ARTE10) in fin were observed in CA1 (p=0.02; d=‐1.25), CA2 (p=0.03; d=‐1.20), CA4‐DG (0.01; d=‐1.34), and SGH (p=0.03; d=‐1.22) Figure 2. Group differences in fsoma were significant in CA1 (p=0.04; d=1.08), CA2 (p=0.02; d=1.22), CA4DG (p=0.04; d=1.10), and SGH (p=0.03; d=0.99). In general, the ARTE10 AD mice had reduced neurite density and elevated soma density in the hippocampal subfields.ConclusionThe results demonstrated that the SANDI model is sensitive to the microstructural alterations in the hippocampal subfields of the animal model with profound AD pathologies.
Local disruptions in non‐rapid eye movement sleep expression are associated with cerebrovascular pathology and worse memory performance in older adults
Authors: Berisha Destiny E , Rizvi Batool , Chappel‐Farley Miranda G. , Dave Abhishek , Meza Novelle J , Sattari Negin , Lui Kitty K. , Chen Ivy Y. , Tustison Nicholas J. , Neikrug Ariel , Benca Ruth M , Yassa Michael A. , Mander Bryce A 
Published: January 2025

AbstractBackgroundAging is associated with disruptions in non‐rapid eye movement (NREM) sleep and memory decline. Cerebral small vessel disease (CSVD) increases with age and is associated with clinical sleep disturbance, but little is known about its relationship with local expression of NREM sleep. Here, we explore associations between CSVD burden, memory, and local electroencephalography (EEG) measures during NREM sleep in older adults.MethodsFifteen cognitively intact older adults (mean age 71.8±6.3 years, 10 female, Apnea Hypopnea Index (AHI) = 7.82±7.95) underwent T2‐weighted fluid‐attenuated inversion recovery magnetic resonance imaging, an in‐lab overnight polysomnography with 128‐channel EEG, and a sleep‐dependent mnemonic discrimination task was administered. Lobar white matter hyperintensity (WMH) volumes were calculated using a validated semi‐automated toolbox. Topographical correlations were run with 5000‐permutation threshold free cluster enhancement.ResultsOlder age was associated with lower absolute posterior total (all p<0.016, r>‐0.61) and slow sigma power (all p<0.018, r>‐0.60) and slow wave activity (SWA) (all p<0.017, r>‐0.61) over centro‐posterior EEG derivations. Age was also positively associated with frontal (t = 0.51, p<0.01) and parietal (t = 0.49, p<0.01) but not occiptal (t = 0.33, p = 0.092) or temporal (t = 0.36, p = 0.064) WMH burden. Occipital WMH burden was also not associated with AHI (t = 0.038, p = 0.843). Occipital WMH burden was associated with global reductions in alpha activity (all p<0.043, t>‐0.78), centro‐posterior reductions in SWA (all p<0.043, t>‐0.63) and Delta (all p<0.009, t>‐0.63), frontal reductions in total (all p<0.043, t>‐0.71) and fast sigma power (all p<0.004, t>‐0.57), global reductions in slow sigma power (all p<0.043, t>‐0.71), and central reductions in theta activity (all p<0.042, t>‐0.57). Better lure discrimination for low similarity lures was significantly positively associated with higher relative slow oscillation expression over fronto‐parietal regions, though this did not survive TFCE correction (all p<0.033, r>0.55).ConclusionsCollectively, these findings indicate that WMH burden in older adults is associated with local disruptions in NREM sleep expression in multiple frequency bands, of which lower frequencies were particularly vulnerable. This in turn may explain weakened memory performance. Future studies should examine the role of NREM sleep expression in cognitive decline associated with CSVD burden.
Mechanistic links of amyloid, atrophy, and cognition profiles for gait disturbance in Alzheimer’s disease
Authors: Baek Min Seok , Seong Joon‐Kyung , Kim Sung‐Woo , Kim Dong Ho , Hong Jin Yong 
Published: January 2025

AbstractBackgroundThis study delves into the relationship between gait disturbances and the progression of Alzheimer’s disease (AD), focusing on how these changes correlate with cognitive impairments and key neuropathological indicators.MethodWe prospectively enrolled 48 patients with AD dementia (ADD), 27 patients with prodromal AD (proAD), and 41 cognitively unimpaired (CU) individuals between January 2022 and May 2023. Participants underwent brain T1‐weighted MRI, 18F‐florbetaben PET, neuropsychiatric tests, and APOE genotyping, and quantified gait analysis was assessed using a 5.79‐m long pressure sensor embed walkway. To evaluate the relationships between gait parameters, cognitive scores, regional amyloid deposition, and regional cortical thickness, Pearson partial correlation coefficients were computed, adjusting for age, sex, education duration, and leg length. Path analysis was employed to test hypothetical models comprising cortical amyloid deposition, cortical thickness, cognition, and gait parameters. Our models hypothesized five main pathways: from amyloid deposition to cortical thickness, cognition, and gait parameters; and from cortical thickness to cognition and gait parameters.ResultAs AD progresses, a significant decline in velocity (p = 0.0144 for comparing CU and proAD; p = 0.0010 for comparing CU and ADD) and step length (p = 0.0033 for comparing CU and proAD; p = 0.0002 for comparing CU and ADD) was observed, indicative of a slower gait pace. The swing time percentage was reduced, and the double support time percentage was increased, showing a significant difference only in ADD patients (p = 0.0015 and p = 0.0007 respectively). Gait variability, reflected in the standard deviations of step length and double support time, escalated with AD progression (p = 0.0173 and p = 0.0143 for comparing CU and ADD, respectively) (Fig. 1). Changes in gait pace, variability, and rhythm were found to be linked to neuroimaging markers of AD, including Aß deposition in widespread areas and cortical atrophy in the inferior parietal and middle temporal gyri, precuneus, and insula (Fig. 2). Path analysis revealed directed relationships between Aß deposition and cognitive impairment, as well as cortical atrophy, collectively impacting gait disturbance in AD (Fig. 3).ConclusionOur analysis indicates directed relationships between amyloid deposition and cognitive impairment, as well as cortical atrophy in these regions, collectively impacting gait disturbance in AD