bluuebunny/crossref_metadata_2025_split huggingface dataset:
The Effect of a Combined Intervention Program Combining Cognitive Training and Physical Activity in Community‐Dwelling Elderly Without Cognitive Impairment
Authors: Shin Ye‐Eun , Han Myeong‐Il , Park Kyung‐Hwan , Choi Mal‐Rye , Sung Nam‐Ju , Kim Sol‐Yi 
Published: January 2025

AbstractBackgroundCombined cognitive training and physical activity has been known to improve brain function. The purpose of this study is to investigate whether combined intervention affects the improvement of cognitive function in the community‐dwelling elderly, and to determine if it improves physical function, such as motor speed and balance.MethodThe study was conducted among community‐dwelling elderly aged 65 years. Participants had no evident cognitive impairment on the Cognitive Impairment Screening Test (CIST), and be physically active. Demographic data was collected, and cognitive function was assessed using a neuropsychological test battery which consists of the Word List Test, Organization Skills, TMT, Word Recall, Boston Naming Test, and orientation. Physical functioning was assessed using the Brief Physical Performance Battery (SPPB), which consists of balance, gait speed, and chair rise assessments. The intervention was a group‐based, combines cognitive training and physical activity and allows to perform simultaneously, with a total of eight sessions, each lasting 60 minutes. Differences were tested between pre‐intervention and post‐intervention scores.ResultA total of 73 participants completed the intervention and were eligible for analysis. After the intervention training, the total score of the neurocognitive test battery increased by 7.32 (±4.20) points (p<0.001) and the SPPB increased by 1.59 (±1.22) points (p<0.001), respectively. In the detailed items of the neurocognitive test battery, word memory was higher in men 3.71 than in women 2.05 (p = .013), and word recall was higher in women 1.44 than in men 0.36 (p = .013), which both reveal significant difference. According to age, orientation was significantly different with a score of 1.45 for those aged 85 years and older than 0.46 for those aged 75‐79 years (p = .044). There were no significant differences in BMI and living arrangements. Multiple regression analysis showed that education (secondary or higher) (p = .008), living arrangement (children) (p = .042), hypertension medication (p = .014), and diabetes medication (p = .015) had a significant effect on neurocognitive performance of this intervention.ConclusionThe results demonstrated that combined intervention improved overall cognitive function and physical performance in community‐dwelling elderly with no apparent cognitive impairment.
Reversal of C9orf72 mutation‐induced transcriptional dysregulation and pathology in cultured human neurons by allele‐specific excision
Authors: Sachdev Aradhana , Gil Kamaljot , Sckaff Maria , Birk Alisha M , Arogundade Olubankole Aladesuyi , Brown Katherine A , Chouhan Runvir S , Lewin Patrick Issagholian , Patel Esha , Keough Kathleen , Conklin Bruce , Smith Alec ST , Clelland Claire 
Published: January 2025

AbstractBackgroundEfforts to genetically reverse C9orf72 pathology have been hampered by our incomplete understanding of the regulation of this complex locus.MethodWe generated five different genomic excisions at the C9orf72 locus in a patient‐derived iPSC line and a WT line (11 total isogenic lines), and examined gene expression and pathological hallmarks of C9 FTD/ALS in motor neurons differentiated from these lines. Comparing the excisions in these isogenic series removed the confounding effects of different genomic backgrounds and allowed us to probe the effects of specific genomic changes. A coding SNP in the patient cell line allowed us to distinguish transcripts from the normal vs. mutant allele.ResultsUsing ddPCR, we determined that transcription from the mutant allele is upregulated at least ten‐fold, and that sense transcription is independently regulated from each allele whereas antisense transcription is regulated by the opposite allele. Surprisingly, excision of the WT allele increased pathologic dipeptide repeat expression from the mutant allele. Importantly, a single allele was sufficient to supply a normal amount of protein, suggesting that the C9orf72 gene is haplo‐sufficient in induced motor neurons. Excision of the mutant repeat expansion reverted all pathology (RNA abnormalities, dipeptide repeat production and TDP‐43 pathology) and improved electrophysiological function, whereas silencing sense expression did not eliminate all DPRs, presumably because of the antisense expression.ConclusionThese data increase our understanding of C9orf72 gene regulation and inform gene therapy approaches, including ASOs and CRISPR gene editing, and provide a therapeutic CRISPR gene editing approach to treat C9 FTD/ALS.
Natural amyloid deposition and neuroinflammation in both brain and eyeball of the old 5xFAD transgenic mouse using Integrated evaluation platform system combining amyloid PET/CT and Macro‐laser light sheet microscopy imaging with tissue clearing
Authors: Son Hye Joo 
Published: January 2025

AbstractBackgroundMacro laser light‐sheet illuminating microscopy (Macro‐LSFM), allied with tissue clearing technologies, herald a transformative paradigm in biomedical imaging, allowing 3D visualization of neuropathologic networks in a transparent intact mouse brain. Moreover, although traditional focus of AD diagnostic has been on CNS pathology, emerging research points to peripheral amyloid‐beta deposition, specifically in the eyeball, as an avenue for investigation. Coupled with conventional [18F]flutemetamol PET/CT imaging, this study leverages the innovative imaging capabilities of Macro‐LSFM with hydrophilic tissue‐clearing technique to elucidate the 3D spatial distribution of AD‐associated neuroinflammation and neuropathologic change both in the brain and eyeball of old transgenic AD mouse.MethodFor thirteen 5xFAD (43 weeks) and seven control mice, we applied a hydrophilic tissue clearing pipelines to extracted brain and eyeball samples, encompassing fixation, clearing, permeabilization, and volume immunostaining using fluorochrome‐conjugated Thioflavin S for β‐amyloid (488 nm), anti‐CD11b for microglia (561 nm), and anti‐ACSA‐2 for astrocytes (647 nm). Macro‐LSFM imaging was performed using a Lightsheet Z.1 microscope (Objective 5x NA 0.16, Zoom 0.75x, single‐mode illumination). 3D volumetric surface models for amyloid, astrocytes, and microglia mapping were generated using Imaris v9.6 software with a minimum surface grain size of 4.0 μm.ResultIn Macro‐LSFM, AD showed significantly higher total surface volumes of amyloid accumulation than control (AD, 898634368 µm³ [383355488‐1324986752]; Control, 33320178 µm³ [11156785‐65390988], p=0.0006). Eyeballs of AD also showed higher amyloid deposits than control (AD, 51091002 µm³ [1002006‐97460784]; Control, 229293 µm³ [8466‐3501462], p=0.0066), showing strong positive correlation of amyloid accumulation between brain and eyeball (R=0.8, p=0.001). AD showed higher anti‐ACSA‐2 specific astrocyte (AD, 59064360 µm³ [27815500‐222619280]; Control 20272722 µm³ [9317288‐27223352], p=0.0047) and anti‐CD11b specific microglial expression (AD, 51210100 µm³ [15309118‐135532144]; Control, 23461593 µm³ [14499170‐27924110], p=0.0162) than control.ConclusionOur synergistic amyloid PET/LSFM approach revealed that active neuroinflammation persists in old AD brain, marked by substantial amyloid deposition, challenging the traditional sequence of early neuroinflammation leading to late‐stage neurodegeneration. Our novel observation of correlated ocular amyloid deposition introduces the eye as a promising, accessible site for the early diagnosis of AD pathology.
Gender Differences in Frontotemporal Dementia: Clinical, Brain Structural, White Matter Hyperintensity, and Brain Metabolic Features
Authors: Chu Min , Liu Li , Nie Binbin , Wu Liyong 
Published: January 2025

AbstractBackgroundGender is a factor influencing the clinical and radiological heterogeneity in dementia. However, gender differences in frontotemporal dementia (FTD) are still underexplored. This study aims to investigate the gender heterogeneity in FTD patients and its association with clinical and imaging features.MethodFTD patients from two independent cohorts were included in this study, one from our center and the other from the Frontotemporal Lobar Degeneration Neuroimaging Initiative (FTLDNI). For clinical characteristics analysis, our center enrolled 64 male and 70 female FTD patients, while FTLDNI selected 91 male and 69 female patients. For brain structural analysis, both our center and FTLDNI included 40 males and 49 females. In the white matter hyperintensity analysis, our center enrolled 21 male patients and 26 female patients, while FTLDNI included 76 male and 61 female patients. In metabolic analysis, only 21 male and 31 female patients were included in our center.ResultIn the Chinese FTD cohort, females had a shorter education year than males, while males had more severe executive dysfunction and hallucinations and agitation symptoms. Males had a higher proportion in the behavioral subtype, while females higher in the language subtype in FTLDNI. Female patients had more significant gray matter atrophy, particularly in the frontal and cingulate regions, compared to male patients. As for white matter hyperintensities, there were no significant differences in quantity and volume between the two genders. Regarding gray matter metabolism, despite females showing more severe gray matter atrophy, they seemed to have better brain reserve function. The atrophy of the left frontal and basal ganglia in females is significantly correlated with cognitive decline, while males exhibit a link between anterior cingulate atrophy and executive dysfunction. Although a significant mediating model was not found, gender has a tendency mediating effect on visual‐vocabulary testing through the fronto‐temporal‐parietal brain region.ConclusionThis study describes the clinical and imaging differences between genders in FTD, which might be attributed to gender influencing different neural circuits. Gender differences need to be considered in precision therapy and clinical trial design.
The effect of sleep apnoea related pathways on longitudinal changes in the brain
Authors: Weihs Antoine , Frenzel Stefan , Ewert Ralf , Stubbe Beate , Penzel Thomas , Fietze Ingo , Bülow Robin , Voelzke Henry , Grabe Hans J. 
Published: January 2025

AbstractBackgroundSleep apnoea is gaining attention as a modifiable risk factor for neurodegenerative disorders, with recent cross‐sectional studies observing associations with advanced brain ageing and increased white matter hyperintensity (WMH) burden. Building upon these findings, we investigate the effects of sleep apnoea on longitudinal changes in brain structural measures using lab‐based polysomnography and 7‐year follow‐up MRI measurements from the general population‐based Study of Health in Pomerania (SHIP).MethodOrdinary least square regression was used. Brain measures (brain age, total brain volume (TBV), mean cortical thickness and WMH at follow‐up) were chosen as outcomes and sleep apnoea metrics (apnoea hypopnea index (AHI), oxygen desaturation index (ODI), arousal index (ARI) and mean oxygen saturation (meanO2) during sleep) as exposures. All models were adjusted for the corresponding baseline MRI metric, follow‐up time, age*sex, intracranial volume and total sleep time (TST). The exposure and all numerical covariates were modelled non‐linearly using restricted cubic splines. AHI, ODI, TST and meanO2 were manually scored according to American Academy of Sleep Medicine standards. ARI was automatically assessed using Sleepware (Phillips, Amsterdam, Netherlands). Structural MRI measurements were segmented using T1‐weighted images in FreeSurfer v7.2. WMH were segmented with the lesion growth algorithm implemented in the LST toolbox v3.0.0 using T1‐weighted and FLAIR sequences. Additionally, brain age scores were generated to represent age‐related structural brain changes.ResultN=387 subjects (47.3% female, baseline age 50.7±12.4 years) with baseline and follow‐up MRI (mean follow‐up time: 7.4±0.6 years) and baseline polysomnography measurements were included. No longitudinal effect was identified when investigating sleep apnoea severity (AHI). Looking at apnoea‐related oxygen desaturation subprocesses, only an inverse relationship was observed between meanO2 and TBV. Exploring sleep fragmentation, a positive effect was observed between ARI and brain age and an inverse effect between ARI and TBV and mean cortical thickness. These effects remained stable when additionally accounting for metabolic, socioeconomic or lifestyle factors.ConclusionUsing longitudinal MRI and lab‐based polysomnography measurements, we found sleep fragmentation to be associated with brain atrophy after 7 years. While further studies are needed, this indicates that sleep fragmentation might be an interesting target to slow the onset of neurodegenerative disorders.
Sars‐Cov‐2 infection and dementia risk: a nationwide, nested case‐control study
Authors: Zur Nika , Stein Nili , Saliba Walid , Weinstein Galit 
Published: January 2025

AbstractBackgroundCognitive impairment following Sars‐Cov‐2 infection is common. We aimed to explore whether covid‐19 is associated with a higher risk of dementia in a nationwide sample of middle‐age and older Israeli adults.MethodThis nested case‐control study was based on electronic health care data from the largest healthcare provider in Israel. From a cohort of 1,145,322 dementia‐free individuals aged ≥50y at baseline (March 2020), we matched subjects with incident dementia to controls without dementia using a density sampling by age, sex, and date of entry to the study, with a ratio of 1 to 10. The follow‐up ended in May 2022. SARS‐CoV‐2 infection was defined based on positive PCR or institutional antigen tests. Conditional logistic regression was used, adjusting for potential confounders including ethnicity, socioeconomic status, comorbidity and smoking. Interaction of covid‐19 with sociodemographic factors and comorbidities were additionally tested. Lastly, the association between covid‐19 severity and dementia were examined, with severity defined as mild without hospitalization, and hospitalization with mild, moderate and severe disease based on hospitalization discharge records.ResultSample mean age was 77.5±9.0 years and 173,668 (57.9%) were females. Overall, 27,280 had incident dementia during the follow up, matched to 272,800 healthy controls. A positive test for covid‐19 was detected among 2,072 (7.6%) cases and 6,722(2.5%) controls. Overall, SARS‐CoV‐2 infection was associated with increased dementia risk (OR = 1.15; 95% CI 1.06‐1.25; P<0.001). There was no increased risk of dementia in those with prior mild covid‐19 who were not hospitalized compared to those without covid‐19 history (OR = 1.003; 95% CI 0.914‐1.101; P = 0.905). However, compared to no covid‐19 history, hospitalization with mild, moderate and severe disease was associated with 83%, 93% and 75% increased risk for subsequent dementia, respectively (OR = 1.833; 95% CI 1.410‐2.382; P<0.001; OR = 1.928; 95% CI 1.366‐2.722; P<0.001; OR = 1.745; 95% CI 1.316‐2.313; P<0.001). Finally, no interactions were observed.ConclusionIn this nation‐based sample, a history of SARS‐CoV‐2 infection was associated with a 15% increased risk for dementia during a 27‐months follow‐up. Increased dementia risk was observed only among covid‐19 patients who were hospitalized. Future investigations with longer follow‐ups are needed to clarify the implications of covid‐19 on brain health.
Proteomics‐Based Prediction of Hippocampal Atrophy in the General Population
Authors: Chen Meilin , Wang Zhibo , Ning Yuye , Jia Jianping 
Published: January 2025

AbstractBackgroundHippocampal atrophy is being characterized as a key biomarker in neurodegenerative disease, especially for dementia. Nevertheless, detecting hippocampus relied on magnetic resonance imaging (MRI), it's very costly and time‐consuming. Our objective is to develop a predictive score to detect MRI‐related hippocampal volume based on large‐scale blood proteomics.MethodThis prospective cohort study utilized data from the UK Biobank, encompassing baseline assessments from 2006 to 2010 and follow‐up data up to September 2023. We focused on 5,680 participants with available Olink blood proteomics data (approximately 3000 proteins) and MRI‐related hippocampal volume. Feature selection and developing predictive score were used a least absolute shrinkage and selection operator (LASSO) regression. Moreover, we tested the prognostic value of the predictive model in the prediction of dementia outcomes in participants without known dementia with over 10‐years follow‐up period.ResultOur predictive score, incorporating 74 distinct proteins, was trained in a cohort of 4,544 individuals and validated in the additional cohort of 1,136 individuals. The predictive score accurately predicted MRI‐related hippocampal volume in the validation cohorts (Figure 1). Based on the predictive scores, we created four groups: high risk, medium risk, low risk, and minimal risk, according to selected cutoff values (10%, 50%, and 90%). The score was effective in identifying individuals at risk of dementia risk, thereby allowing stratification to different risk groups for dementia incidence. The hazard ratio for dementia incidence in the minimal risk group was 0.04 [95%CI: 0.02‐0.06] compared with the high‐risk group (Figure 2). Moreover, the predictive score was still effective in identifying individuals at risk of dementia risk in the independently cohort of 45,000 participants.ConclusionThe predictive scores, based on simple blood proteins, accurately predicts hippocampal volume and assesses the risk of dementia incidence. The score may enhance early screening for hippocampal atrophy and provide guidance for preventive care in early dementia.
Spatial Similarity of Person‐Specific Resting State Topography in Cognitive SuperAgers
Authors: Diamond Bram R , Martersteck Adam , Rogalski Emily J 
Published: January 2025

AbstractBackgroundMemory decline in late life is a common hallmark of aging, yet SuperAgers are individuals age 80+ with episodic memory performances at least as good as cognitively average 50‐to‐60‐year‐olds. Recent work, combining anatomical and functional MRI, has shown the precise boundaries of large‐scale resting state networks vary at the individual level. Further, the use of person‐specific rather than standard parcellations has led to more behaviorally meaningful associations, and has not been explored in SuperAgers. The current project examines whether the topography of person‐specific resting state networks differ between SuperAgers and older‐aged controls (OACs).MethodsTwenty‐four SuperAgers and 16 OACs were included in the study. SuperAger/OAC phenotype was determined based on measures of episodic memory, executive functioning, verbal fluency, and picture naming across two visits, separated by at least 18 months. Person‐specific network parcellations were derived for each participant using their first visit resting state fMRI connectivity, constrained by anatomical priors, with a Multi‐Session Hierarchical Bayesian Model (MS‐HBM; Kong et al., 2021). Sørensen‐Dice spatial similarity coefficients (Dice) were calculated to determine the within‐group spatial similarity of each network. Dice was defined as the number of overlapping vertices between two participants’ network segmentation, multiplied by two, and divided by the sum of vertices in both network segmentations. Dice was calculated for each participant compared to all other within‐group participants and averaged to create a Dice score per participant per network. Dice scores for each of the 17 person‐specific networks were compared between SuperAgers and OACs using Mann‐Whitney tests, Bonferroni‐corrected.ResultsDemographics did not differ significantly between groups. Person‐specific network topography varied between participants (Figure 1). SuperAgers had significantly lower Dice scores than OACs in six of 17 networks (Figure 2; p‐value ≤ 0.0029).ConclusionCompared to OACs, SuperAgers demonstrated greater within‐group variability in resting state network topography. Greater spatial variability may reflect unique patterns of functional or structural topography that support SuperAgers’ exceptional memory abilities. Future investigations will include further examination of the functional connectome of SuperAgers, leveraging the precision approach employed here.
Unsupervised Learning‐based Drug Repositioning for Alzheimer’s Disease Targeting Brain Cell Type Specific Genetic Subtypes
Authors: Mishra Ankit Kumar , Sahelijo Nathan J , Priyadarshi Dhawal , Jun Gyungah R 
Published: January 2025

AbstractBackgroundAlzheimer’s disease (AD) presents challenges with its complex neurodegenerative mechanisms, leading to a high failure rate in clinical trials. While drug repositioning offers a cost‐effective solution, the lack of a subtype‐driven strategy hinders success. Previously, we defined genetic subtypes and their prioritized genes for each genetic subtype (Sahelijo et al., 2022). This study evaluated unsupervised learning algorithms to characterize existing compounds targeting prioritized genes for the genetic subtypes.MethodCompounds in at least Phase 2 clinical trials were gathered from PubChem. Active compounds against subtype‐specific genes were selected, and their structural data were transformed into pharmacophore fingerprints using ChemmineR. Unsupervised algorithms (Agglomerative Clustering, Ensemble Clustering, Gaussian Mixture Models, Bayesian Gaussian Mixture Models) were optimized using evaluation metrics (Calinski‐Harabasz, Davies‐Bouldin, Silhouette) to cluster compounds within each subtype with the optimal cluster number and optimal algorithm. The finalized clusters of compounds were evaluated using significance values and mean within‐cluster Jaccard similarity scores and were characterized with target genes and mechanisms of action.ResultFour of the nine genetic subtypes generated compound clusters, including 3 clusters using Agglomerative Clustering for Ast‐M2 with 11 targets and 180 compounds, 2 clusters using BGMM for Ast‐M9 with 14 targets and 341 compounds, and 4 clusters using Ensemble Clustering for Oli‐M45 with 11 targets and 66 compounds and for Oli‐M50 with 18 genes and 431 compounds. We observed common structural signatures between Ast‐M2, Ast‐M9, and Oli‐M50 clusters, while Oli‐M45 clusters did not share any signatures with other clusters. The most significant cluster was found for the Oli‐M45 subtype, with a cluster significance value of 8.49 and the highest mean compound similarity score of 0.96. The top‐ranked cluster primarily contained Vinblastine formulations—microtubule and tubulin polymerization inhibitors—targeting TUBA1A and TUBA1B.ConclusionWe demonstrated a novel drug repositioning framework for AD using unsupervised learning algorithms, enabling precision medicine and subtype‐driven repositioning. This framework will be implemented in our future software tools.