bluuebunny/crossref_metadata_2025_split huggingface dataset:
Analysis of Time‐Delayed Effective Connectivity for Normal Cognition and MCI under Motion Detection Tasks: an EEG Study
Authors: Sun Boxin , Deng Jinxian , Renli Alina Brighty , Kavcic Voyko , Ren Jian , Giordani Bruno , Zhang Rong , Li Tongtong 
Published: January 2025

AbstractBackgroundExisting work suggested that AD pathology can affect the direction and intensity of information signaling in functional brain regions. The present study evaluates the time‐delayed effective connectivity of normal controls (NC) and patients with mild cognitive impairment (MCI) under motion‐detection tasks and explores identification of possible anomalies and deviated patterns in effective connectivity associated with AD pathology.MethodOur research focuses on task‐based EEG (64‐channel), where participants were asked to perform a motion direction discrimination task. The current dataset includes 56 consensus‐diagnosed, community‐dwelling African Americans with subjective cognitive complaints (ages 60‐90 years, 28 normal controls (NC) and 28 MCI patients) recruited through the Wayne State Institute of Gerontology and Michigan Alzheimer’s Disease Research Center.The successive motion‐task performance periods examined include: (I) stimulus onset to Go/No‐Go indication, (II) Go (or No‐Go) indication to motion‐stop, and (III) the Button‐Press period. For each period, we evaluated the time‐delayed effective connectivity across all the possible EEG region pairs using causalized convergent cross‐mapping (cCCM) of the current source density. For each region pair, the delay (within 50ms) that results in the largest cCCM value (which reflects the intensity of the information flow) is taken as the dominant delay. Within the NC/MCI group, the directed signaling path (with cCCM value > 0.7) that appears in more than 80% of the participants is defined as a common active path of the group.ResultOur analysis shows that: (i) Delayed effective connectivity is noticeably stronger than its zero‐delay counterpart, indicating the existence of non‐zero transmission delays in inter‐region information transfer; (ii) NC and MCI may share common active paths, but each group has their own, unique common paths; (iii) Both NC and MCI groups have fewer common active paths in the Go and Button‐Press periods than during the stimulus onset and No‐Go periods, which may imply that brain effective connectivity is more focused during task execution.ConclusionTime‐delayed effective connectivity analysis may enable identification of possible signaling pathways in the brain and of dissimilarities in pathway usage between NC and MCI associated with AD pathology.Funding: NSF‐2032709/Li; NIH‐1R21AG046637‐01A1/Kavcic; NIH‐1R01AG054484‐01A1/Kavcic; NIH‐P30AG072931/Paulson; NIH‐P30AG024824/Yung.
Whole genome methylation sequencing in blood identifies extensive differential DNA methylation in mild cognitive impairment (MCI)
Authors: Madrid Andy , Breen Coleman E , Papale Ligia A , Clark Lindsay R. , Asthana Sanjay , Johnson Sterling C. , Keles Sündüz , Hogan Kirk J. , Alisch Reid S 
Published: January 2025

AbstractBackgroundWhole genome methylation sequencing (WGMS) in blood identifies extensive differential DNA methylation between persons who are cognitively unimpaired (CU) and those with late‐onset dementia due to Alzheimer’s disease (AD). Here we investigate differentially methylated positions (DMPs) in persons with mild cognitive impairment (MCI) compared to persons with and without AD.MethodWGMS data quantified DNA methylation levels at 25,406,945 CpG loci in 382 blood samples from 99 persons with MCI, 109 persons with AD and 174 cognitively unimpaired persons in the Wisconsin Alzheimer’s Disease Research Center (WADRC) and the Wisconsin Registry for Alzheimer’s Prevention (WRAP). Beta‐binomial models were developed to test for significant DNA methylation levels between groups, accounting for batch effects, estimated white blood cell proportions, sex, body mass index (BMI), and age. P‐values were corrected and a local false discovery rate (lFDR) was computed.ResultWGMS identified 10,262 MCI‐associated DMPs (Figure 1). We identified 1,984 genes comprising one or more DMPs (e.g., ACE, ANK3, and HLA‐DQA1) encode proteins that participate in biological pathways relevant to neuronal function including synapse organization, dendrite formation and potassium ion transmembrane transport. Interrogation of DMPs among all two‐group comparisons (i.e., MCI:CU, AD:CU, and AD:MCI) identified 65 overlapping DMPs (Figure 2). Twelve of the overlapping DMPs are associated with 4 genes. Neighboring TDG and C12orf73 share 10 DMPs on chromosome 12q23.3, FHIT and RXFP1 comprise 1 DMP each. The remaining shared 53 DMPs are intergenic. We further investigated DMPs with progressive changes in DNA methylation levels from CU to MCI to AD. We identified 570 DMPs with increasing or decreasing DNA methylation levels were identified, including DMPs in enhancer‐promoter interactions in genes previously associated with AD, including KANSL1 (Figure 3).ConclusionWGMS identifies differentially methylated CpGs in known and newly detected genes and enhancers in blood from persons with and without MCI and AD and reveals progressive dysregulation of DNA methylation levels between CU, MCI, and AD.
Effects of Intermittent Theta Burst Preconditioning on 40Hz Gamma Wave Synchronization
Authors: Ahn Donghyun , Roh Sungwon , Lee Haram , Kim Haein , Lee Youngseok , Jeon Jin Yong 
Published: January 2025

AbstractIn the treatment of Alzheimer’s disease (AD), traditional 40Hz gamma wave stimulation, while effective in improving cognitive function, has been limited by the lengthy duration of treatment. To address this, our study sought to enhance the time efficiency of 40Hz stimulation by utilizing intermittent theta‐burst stimulation (iTBS) as a pretreatment. Experiments were conducted on AD mouse models, divided into four groups: no stimulation, 40Hz stimulation only, iTBS stimulation only, and combined iTBS and 40Hz stimulation. The groups were assessed for cognitive function and behavioral changes, as well as neuro‐pathological indicators.The results revealed that the group receiving combined iTBS and 40Hz stimulation showed significant improvements in cognitive function and behavior from the fifth day of treatment, compared to the groups receiving only a single type of stimulation. This indicates that the combined stimulation is not only effective but also significantly reduces the treatment time, demonstrating rapid effects. Therefore, the combination of iTBS and 40Hz stimulation presents a new approach in AD treatment, enhancing both time efficiency and therapeutic effectiveness. These findings offer important implications for future clinical research and applications.
Preclinical efficacy and rationale of targeting lysine280‐acetylated tau for Alzheimer’s disease therapy with ADEL‐Y01, humanized monoclonal antibody
Authors: Kim Min‐Seok , Song Ha‐Lim , Kim Na‐Young , Mun Yeon‐Seon , Kim Dong‐Hou , Yoon Seung‐Yong 
Published: January 2025

AbstractBackgroundThe spatiotemporal pattern of the spread of pathologically modified tau through brain regions in Alzheimer’s disease (AD) can be explained by prion‐like cell‐to‐cell seeding and propagation of misfolded tau aggregates. Hence, to develop targeted therapeutic antibodies, it is important to identify the seeding‐ and propagation‐competent tau species. The hexapeptide 275VQIINK280 of tau is a critical region for tau aggregation, and K280 is acetylated in various tauopathies including AD. However, the mechanism that links tau acetylated on lysine 280 (tau‐acK280) to subsequent progression to neurodegenerative disease remains unclear. Here, we demonstrate that tau‐acK280 is critical for tau propagation processes including secretion, aggregation, and seeding.MethodWe developed an antibody, Y01, that specifically targets tau‐acK280, tested its efficacy in vitro and in vivo tauopathy models, and solved the crystal structure of Y01 in complex with an acK280 peptide.ResultUpon interaction with acetylated tau aggregates, Y01 prevented tauopathy progression and increased neuronal viability in neuron cultures and in tau transgenic mice through antibody‐mediated neutralization and phagocytosis, respectively. Crystal structure confirmed that Y01 directly recognizes acK280 and the surrounding residues.ConclusionBased on our observations that tau‐acK280 is a core species involved in seeding and propagation activities, the Y01 antibody that specifically recognizes acK280 represents a promising therapeutic candidate for AD and other neurodegenerative diseases associated with tauopathy. ADEL‐Y01 is currently undergoing a phase‐1 clinical trial in the United States through a collaborative effort between ADEL and Oscotec.
Polyphenols derived from Sorghum bicolor grains exhibit the ability to alleviate amyloid beta in Alzheimer’s Disease
Authors: Abdulraheem Rasheed A. , Bharadwaj Prashant , Li Zhaoyu , Coorey Ranil , Johnson Stuart , Martins Ralph N , Fernando Warnakulasuriya Mary Ann Dipika Binosha 
Published: January 2025

AbstractBackgroundAccumulation of amyloid beta 42 (Aβ42) senile plaques is the most critical event leading to Alzheimer’s disease (AD). Currently approved drugs for AD have not been able to effectively modify the disease. This has caused increasing research interests in health beneficial nutritious plant foods as viable alternative therapy to prevent or manage AD. Sorghum bicolor presents strong antioxidants, anticancer, anti‐inflammatory and antidiabetic properties. However, there is no published data on how this widely available and cost‐effective food could benefit people living with AD.MethodPolyphenols were extracted from three Sorghum varieties with black, reddish‐brown, and red pericarp. The individual polyphenols compounds were identified using an Agilent 1290 infinity 2 UHPLC system coupled to an Agilent 6475 LC‐QQQ LC‐MS/MS. The polyphenol extracts were screened using in‐silico, MC65 cell and Caenorhabditis elegans AD models. The activities of the extracts against Aβ42 aggregation were analyzed using molecular docking, fluorescence, toxicity, and healthspan assays.ResultThrough the application of molecular docking, polyphenols extracted from Sorghum bicolor grains were identified for their potential to inhibit Aβ42 aggregation. Positive interactions were observed between the polyphenols and Aβ42. Cell studies indicated increased viability of MC65 cells, possibly attributed to the inhibition of Aβ42 aggregation. In the Alzheimer’s disease model of Caenorhabditis elegans, enhanced body bending, and pharyngeal pumping were observed compared to controls, suggesting a reduction in pathology. The order of activities was found to be red pericarp < reddish‐brown pericarp < black pericarp sorghum.ConclusionThe polyphenol extracts from black pericarp Sorghum bicolor grain could be a candidate ingredient in the development of complementary dietary supplement for AD therapy. Future investigation include lifespan, and fluorescence imaging to unravel the mechanisms underlying the observed health benefits prior to study in AD animal models.
Prefrontal cortex functioning in simple and choice stepping in older adults with mild to moderate dementia – A functional near‐infrared spectroscopy (fNIRS) cross‐sectional study
Authors: Chan Wayne LS , Yeung Michael KC , Tam Yee Kiu , Tang Pui Man , Wong Ka Chun , Wong Ka Long , Wong Lok Yiu 
Published: January 2025

AbstractBackgroundOlder adults with dementia have a high fall risk. Choice stepping (i.e., being able to execute rapid, accurate and efficient steps to reach a designated target) is an important indicator of the risk of falls in older adults. Choice stepping performance is determined by both physical (e.g., dynamic balance) and cognitive function (e.g., executive function). The prefrontal cortex may play an important role in mediating choice stepping performance. However, the prefrontal cortex activity of older adults with dementia in choice stepping is unclear.This study aims to evaluate and compare the activity of the prefrontal cortex in simple and choice stepping in healthy older adults and older adults with mild to moderate dementia.MethodsThis study was a cross‐sectional study. Twenty‐nine healthy older adults and 28 older adults with a diagnosis of mild to moderate dementia who could walk for 10 meters independently were recruited. Hemodynamic changes occurring in the participants' prefrontal cortices during simple and choice stepping were recorded by multichannel fNIRS. Choice stepping reaction time test was used to evaluate the choice stepping performance of the participants.ResultsThe choice stepping reaction time of the dementia group was significantly higher than that of the healthy control group (p < .001). The activations of several areas of the prefrontal cortex (left dorsolateral, left ventrolateral, left and right orbitofrontal cortices) during choice stepping tasks were significantly increased in the dementia group compared to the control group (all p < .047). A significantly higher activation in the right frontopolar cortex was also found in the choice stepping task compared to that in the simple stepping task in the dementia group (p = .040).ConclusionOlder adults with mild to moderate dementia showed a higher prefrontal cortical activation during choice stepping compared to healthy older adults. Choice stepping may demand more on the executive function of older adults with mild to moderate dementia compared to healthy older adults. Further studies using a larger sample size are required to explore the prefrontal cortical activity during different stepping tasks in older adults with dementia.
Multidimensional Modeling of Biological Aging: Integrating Gait, Eye Movement, Rest‐State Functional Connectivity, and Plasma Biomarkers in non Dementia Elderly Individuals
Authors: Lin Jingyi , Ouyang Ziyu , Xu Tianyan , Shen Lu , Jiao Bin 
Published: January 2025

AbstractBackgroundAging exhibits significant variation among individuals, with biological age as a more reliable predictor of current health status compared to chronological age. Predicting biological age is crucial for facilitating timely interventions aimed at improving the adaptation to the aging process. Given the intricate and multifactorial nature of aging, a scientific approach involves constructing a prediction model for biological age that incorporates multiple dimensions systematically.MethodThis study enrolled 908 non‐dementia elderly participants, and their eye movement, gait, rest‐state functional connectivity (rs‐FC), and plasma GFAP and NfL level were measured. These parameters were used to assess an individual's biological age using logistic regression.ResultWe identified 26 gait features, 2 eye‐tracking features, 19 rs‐FC features, and plasma GFAP level that exhibited significant correlations with age (p<0.05). Initially, prediction models were constructed separately using different categories of indices. Notably, gait features demonstrated robust prediction performance for age (R2=0.783; MAE=1.852). Subsequently, combining all indicators for the prediction model resulted in an exceptional level of performance (R2=0.939; MAE=1.080).ConclusionA quantitative model of biological age was successfully constructed from a multi‐dimensional and systematic perspective, proving effectiveness in predicting an individual's biological age. This comprehensive approach, incorporating diverse indices, enhances the accuracy and reliability of age prediction models.
Non‐invasive quantification of [18F]‐PI‐2620 binding to tau deposits in the brain using an image‐derived input function
Authors: Bhattarai Anjan , Holy Emily Nicole , Wang Yiran , Spencer Benjamin A. , Wang Guobao , DeCarli Charles S. , Fan Audrey P. 
Published: January 2025

AbstractBackgroundThis study quantified tau binding in the brain with 18F‐PI2620 PET using a non‐invasive Image‐Derived Input function(IDIF), derived using a new total‐body EXPLORER PET/CT scanner (Spencer et al.,2021). Additionally, we explored how PET scan duration influences the quantification of kinetic parameters across brain regions of interest(ROIs) that are vulnerable in Alzheimer’s Disease.MethodThe study cohort included 15 individuals (10 cognitively unimpaired, 3 mild cognitive impairment, and 2 AD; ages=68‐92 years; all tau negative) from the UC Davis ADRC. Dynamic total‐body 18F‐PI‐2620 PET images were acquired over 90 minutes using the uEXPLORER (resolution=2.344 mm isotropic voxels, framing protocol:30×2s,12×10s,7×60s,16×300s). Brain cropped PET images were motion corrected (Jenkinson et al.,2002), and linearly registered to individual T1‐weighted(T1W) MRIs (Jenkinson & Smith, 2001). Grey matter ROIs, including the medial temporal(MT), posterior cingulate(PC), and lateral parietal(LP) cortices, were obtained parcellating T1W images (Desikan et al.,2006).Dynamic time activity curves for each brain ROI were fitted to a reversible two‐tissue compartmental model(2TCM), accounting for delay, using a subject‐specific IDIF(plasma and metabolite‐corrected) derived from the descending aorta of the same images (Figure 1). ROI‐specific micro and macro kinetic parameters were estimated. Logan graphical analysis (Logan,2000) was also used to estimate total distribution volume(VT).Result2TCM with IDIF demonstrated high‐quality fits of 18F‐PI2620 binding across grey matter ROIs (Figure 1). Perfusion (K1) was observed to be reduced in MT compared to PC and LP (Figure 2A).All kinetic parameters remained relatively stable after the 60‐minute scan window across all ROIs. Notably, K1 showed stability after 30 minutes of scan duration across all ROIs (Figure 2 and 3).A strong correlation was observed between VT estimated using 2TCM and Logan plot analysis, across all ROIs LP(r=1.00, p<0.001), MT(r=0.96, p<0.001), PC(r =1.00, p<0.001).Additionally, significant negative correlation was observed between binding potential and perfusion across all ROIs (r=‐0.40, p=0.007).ConclusionThis study highlights the utility of a non‐invasive descending aorta IDIF derived using a total‐body EXPLORER PET/CT scanner to quantify 18F‐PI‐2620 grey matter kinetics. Preliminary findings suggest that a 60‐minute scan window may be sufficient for reliable quantification of kinetic parameters, while a 30‐minute scan time may suffice for perfusion alone. These findings warrant validation in a cohort involving tau positive individuals.
Neural Correlates of Dual‐Functional Local Dynamic Stability in Older Adults
Authors: Zhou Sa , Lin Feng Vankee 
Published: January 2025

AbstractBackgroundTo maintain local dynamic stability (LDS), both cognitively and physically, without being interfered with by internal or external disturbance is important for functional independence but declines as ages. However, some older adults are capable of high dual‐functional LDS. Understanding the brain differences between these older adults and their counterparts may help discover protective mechanisms for functional independence in old age. The purpose of the study was to compare the brain topology between older adults with heterogenous dual‐functional LDS.MethodCognitively and physically healthy older individuals (n = 52) were recruited and categorized into four groups (low cognitive/low physical, low cognitive/high physical, high cognitive/low physical, and high cognitive/high physical LDS groups) based on the intra‐individual variability of performance in selected cognitive and physical tasks relying on speed processing and attention. Brain topology was measured via diffusion tensor imaging and quantified with clustering coefficients reflecting segregation and characteristic path lengths reflecting integration, respectively, based on graph theory methods.ResultAfter correcting for multi‐comparison, the high dual‐functional LDS group exhibited significantly higher integration between the inferior frontal and postcentral areas but lower integration between the frontal and temporary areas within the left hemisphere, compared to the other three low cognitive/physical stability groups.ConclusionIntegration in selective brain networks may contribute to maintaining the dual‐functional LDS in older adults.
Genetics, atrophy, liquid biomarkers and cognitive tests in Alzheimer’s disease: an integrated and multimodal analysis pipeline to understand the neurodegenerative mechanisms
Authors: Squillario Margherita , Reggiani Francesco , Pardini Matteo , Piana Michele 
Published: January 2025

AbstractBackgroundAlzheimer’s disease (AD) is the most common neurodegenerative disease among the elderly (50–75%) and the causes of the sporadic form are not yet clear. The genetic predisposition is relevant (60–80%), but alone is not sufficient to trigger those initial processes that lead to neurodegeneration and to the slowly atrophy of the brain. Several public datasets containing multimodal data centered on AD have emerged since the beginning of 2004 when ADNI come out. An appropriate integration of various data types (e.g., biomedical images, GWAS/WES, cognitive tests, liquor protein expression) is pivotal to understand this phenomenon.MethodsObjective 1: we will develop a merged multimodal AD‐centered dataset from a careful selection of public database. Objective 2: we will develop a user‐friendly analysis tool starting from the multikernel/deep learning pipeline devised to properly address the analysis of multimodal data. Objective 3: in the merged multimodal AD‐centered dataset we will evaluate the predictive performance of gene‐SNPs panels, retrieved from the literature, using the developed tool. We will identify clusters of genes‐SNPs (of the panel) and of specific neurodegenerative markers correlating with the atrophy (measure by FDG‐PET) of the most affected brain regions through a weighted correlation network analysis (WCNA). Objective 4: we will validate those clusters in silico, in an independent partition of the merged multimodal dataset and/or in independent AD public dataset.ResultsThe analysis of the merged multimodal AD dataset with the proper multimodal‐oriented tool, will identify genes‐SNPs signatures that correlate with atrophy starting from (i) promising genes‐SNPs panels identified in the literature and (ii) neurodegenerative biomarkers (identified in cognitive tests, abundance protein dataset, imaging data) that correlate more strongly with atrophy.ConclusionsThe final aim of the integrated multimodal dataset explored with the multimodal‐oriented analysis tool is to verify the existence of endophenotypes characterizing groups of AD patients defined based on the different brain‐region atrophic component.