bluuebunny/crossref_metadata_2025_split huggingface dataset:
The Prevalence and Impact of Vertebral Artery Hypoplasia on Cerebral Hemodynamics
Authors: Fico Brandon G. , Moir M. Erin , Loggie Nicole A. , Gaynor‐Metzinger Sarean Harmoni A. , Miller Kathleen B. , Norby Alex M. , Rivera‐Rivera Leonardo A. , Howery Anna J. , Rowley Howard A. , Johnson Kevin M. , Johnson Sterling C , Wieben Oliver , Barnes Jill N. 
Published: December 2023

AbstractBackgroundVertebral artery hypoplasia (VAH) is an anatomical variation that may be associated with lower cerebral blood flow. We demonstrated the prevalence of VAH to be approximately 26% in a pilot study of healthy adults (n = 39). The purpose of this study was to expand on these findings by determining the prevalence of VAH and its impact on cerebral hemodynamics in a larger sample size of middle‐aged and older adults.MethodA total of 550 participants (66 ± 9 years; 346 females) underwent 4D flow MRI scans to evaluate the internal carotid arteries (ICA), vertebral arteries, and basilar artery. VAH+ (positive for VAH) was determined from the 4D flow MRI scans using both diameter (<2.5 mm) and flow (<47 mL/min).ResultWe identified 152 participants as VAH+ (prevalence of 28%). The prevalence of VAH+ was similar between females (n = 95; 27%) and males (n = 57; 28%). VAH predominantly occurred in the right vertebral artery (n = 102; 67%). As expected within VAH+ participants, the hypoplastic vertebral artery diameter was smaller (2.0±0.2 mm vs. 2.8±0.5 mm; p<0.001), blood flow was lower (29±10 ml/min vs. 100±44 ml/min; p<0.001), and pulsatility index was higher (1.8±0.6 a.u. vs. 1.3±0.3 a.u.; p<0.001) compared to the contralateral artery. There were no differences in ICA diameter (p = 0.875), blood flow (p = 0.553) or pulsatility index (p = 0.984) between VAH+ and no VAH. When evaluating the basilar artery, the diameter was smaller (2.7±0.4 mm vs. 2.8±0.4 mm; p = 0.037) with lower blood flow (105±35 ml/min vs. 116±37 ml/min; p<0.001) in VAH+ compared with no VAH. Males with VAH+ had higher basilar artery pulsatility index compared with males with no VAH (1.4±0.4 a.u. vs. 1.2±0.3 a.u.; p = 0.004), but this was not apparent in females (p = 0.544). When comparing global cerebral blood flow, there was a trend for lower flow in VAH+ compared with no VAH (p = 0.096).ConclusionWe demonstrated VAH prevalence to be around 28%, with similar prevalence in both males and females. VAH was associated with impaired regional flow and with elevated basilar artery cerebral pulsatility in males.
The association of gait velocity and cognitive performance in a sample of older Chinese Americans: A pilot study
Authors: Yang Xiao , Spat‐Lemus Jessica , Xia Tianxu , Cai Dongming , Lai Randy , Neugroschl Judith A. , Aloysi Amy , Zhu Carolyn W , Sano Mary , Akrivos Jimmy , Huang QiYing , Zeng Xiaoyi , Liu Linghsi , Li Clara 
Published: December 2023

AbstractBackgroundGait velocity and cognition generally decline as individuals age. Studies have indicated that gait velocity can be used as a simple, novel, and relatively culture‐free cognitive assessment tool in older adults, particularly in domains of memory, attention, and executive function. There is limited research in this area with racial/ethnic minority groups. This study examined the association between performance on specific cognitive domains and gait velocity in older Chinese Americans – a growing, yet underrepresented group in US‐based research.Method71 Chinese American older adults (age 73.6 ± 6.9) with normal cognition (n = 27), mild cognitive impairment (n = 32), and early dementia (n = 12) were included in a pilot study at the Alzheimer’s Disease Research Center (ADRC) at Mount Sinai. Participants underwent a standard dementia evaluation in Mandarin/Cantonese, which included a clinical interview, medical exam, and neuropsychological testing. All participants self‐reported as Chinese Americans who were primarily Cantonese‐ or Mandarin‐speaking. Exclusion criteria included: not proficient in Cantonese/Mandarin, mobility impairment, as well as history of psychiatric disorder(s) and cerebrovascular accident. Diagnoses were assigned at a consensus conference. Exploratory factor analysis was conducted to determine cognitive domains encompassing the neuropsychological battery, which included tests of processing speed/attention, executive function, memory, and language/verbal fluency. Gait velocity was measured with a walking speed test measured in seconds. Multiple linear regression was used to examine the association between gait velocity and cognitive performance, while controlling for age, education, depression measured by Geriatric Depression Scale (GDS), and lifestyle/medical factors (e.g., tobacco/alcohol use, hypertension).ResultFactor analysis demonstrated 4 principal neuropsychological factors: non‐contextual memory, contextual memory, processing speed, and language/verbal fluency. The regression model showed that lower scores on a test of non‐contextual memory was associated with slower gait velocity. Higher GDS scores were associated with slower gait velocity.ConclusionConsistent with previous studies with predominately non‐Hispanic White samples, we found an association between gait velocity and non‐contextual memory in older Chinese Americans. In contrast to the literature, no other cognitive domains were significant in this small sample. The finding provides preliminary data to support the use of gait velocity as a novel cognitive assessment in this historically underrepresented group.
Impaired KATP channel‐mediated electro‐metabolic signaling in capillary pericytes disrupts brain blood flow control in aging and Alzheimer’s disease
Authors: Hariharan Ashwini , Longden Thomas Andrew ,   Longden lab of neurovascular interactions in health and disease
Published: December 2023

AbstractBackgroundAging is associated with a gradual decrease in cerebral blood flow and disruptions in neurovascular coupling, causing a mismatch of energy supply and demand that can precipitate neuronal dysfunction and cognitive decline. We have recently discovered that ATP‐sensitive K+ (KATP) channels in capillary thin‐strand pericytes act as metabolic sentinels that couple subtle changes in local glucose to electrical signals such that blood flow is rapidly adjusted in response to decreased availability of this critical energy substrate. Aging and Alzheimer’s disease (AD) are linked to an increase in caveolin, association with which can disrupt the ability of KATP channels to sense intracellular energy state by decreasing sensitivity to ADP. Here, we demonstrate than an interaction between caveolin and KATP channels in aging animals underlies the loss of electro‐metabolic blood flow control by brain pericyte KATP channels.MethodUsing a combination of advanced techniques such as in vivo two‐photon laser scanning microscopy to image hemodynamics, and electrophysiological recordings from isolated cortical thin‐strand pericytes, we determine the effect of aging and familial AD on brain blood flow control by pericyte KATP channels in young (2‐3 months old) and aged (12‐14 months old) 5xFAD mice. We investigate the interaction between caveolin and KATP channels, and whether disrupting caveolae can restore the energy sensing abilities of pericyte KATP channels in older mice.ResultIn young mice, inhibiting glucose import into the brain with a glucose transporter‐1 blocker (1 µM BAY‐876) activates pericyte KATP channels to dilate arterioles and capillaries, and increase blood flow. Remarkably, this effect is completely lost in older mice. Our data reveal a key interaction between caveolin and KATP channels underlies this dysfunction, and disrupting caveolae in older mice reinstates the ability of pericyte KATP channels to sense decreases in local glucose.ConclusionThin‐strand pericytes protect neuronal health by coupling local energy substrate availability with hyperemia, and the disruption of this mechanism can contribute to the development of blood flow dysregulation observed in dementia. Our data unveil a role of caveolin in the loss of energy sensing by pericyte KATP channels, which can be leveraged to augment blood flow in aging individuals.
Cross‐cultural adaptation, validity and reliability of the Everyday Cognition Scale in Mexico M‐ECog in Older Adults with Subjective Cognitive Decline, Mild Cognitive Impairment and Alzheimer’s Dementia
Authors: Mimenza Alberto , Pillajo Brenda , Gutiérrez Lidia Antonia , Trejo Natalia Arias , Aguilar‐Navarro Sara Gloria 
Published: December 2023

AbstractBackgroundThe Everyday Cognition (ECog) scale was created to assess the functional abilities of older adults across a wide range of abilities between normal aging and dementia. The original ECog was shown to have convergent and divergent external validity. Developed in 2008 by Farias et al and updated in 2021. This scale screens early cognitive alterations such as Subjective Cognitive Decline (SCD), Mild Cognitive Impairment (MCI) and Alzheimer’s dementia (AD) through the decline of basic activities and instruments of daily life (DLA)To establish validity, reliability, and cross‐cultural adaptation of the ECog in Spanish (M‐ECog) to identify: SCD, MCI, and Alzheimer’s‐type dementia in older Mexican adults.Method200 patients and 200 informants in a memory clinic of a third level hospital in Mexico City. Four groups were formed: 50 cognitively healthy (CH), 50 SQD, 50 MCI and 50 AD. The clinical evaluation included: sociodemographic aspects, cognitive status by the Mini‐Mental State Evaluation (MMSE) and Montreal Cognitive Evaluation Spanish version (MoCA‐E). The informants rated the functional status measured through the KATZ and Lawton & Brody scales, as well as the ECog Spanish version (M‐ECog).ResultThe internal consistency of the overall function of the M‐ECog (Cronbach’s alpha) was 0.881. The intraclass correlation coefficient was 0.877 (95% CI, 0.850‐0.902; p<0.001). M‐ECog was significantly correlated with DLA 0.40 (95% CI, 0.320‐0.471; p<0.001), MMSE 0.68; (95% CI, 0.650‐0.710; p<0.001) and MoCA‐E 0.70 (95% CI, 0.620‐0.892; p<0.001). And it differentiated patients with SCD, MCI and AD from CH (p < 0.002). The area under the curve (AUC) for SQD was 0.70 (95% CI, 0.58‐0.82), p < 0.005 with a cut‐off value of 46 points, (Sensitivity (S) 99%, and Specificity (E) of 96%; the AUC for MCI was 0.94 (95% CI, 0.89‐0.99), p < 0.001 with a cut‐off point of 52 points, (S: 97%, E: 27%); and for the dementia group, the AUC was 0.86 (95% CI, 0.79‐0.92), p <0.001 with a cut‐off value of 85 points, with (S: 97%, E: 51%).ConclusionM‐ECog is a valid, reliable, useful instrument that measures daily skills mediated by cognition in older Mexican adults, self‐applicable (patients and informants) with SCD, MCI and Alzheimer’s Dementia
Re‐calibration and performance of a proteomic prognostic test for 5‐year dementia risk
Authors: Paterson Clare , Loupy Kelsey , Biegel Hannah , Hagar Yolanda , Ostroff Rachel , Sampson Laura , Bogren Lori K , Williams Stephen A 
Published: December 2023

AbstractBackgroundProteomics‐driven health and wellness tests can provide personalized insight into individual risk for disease that is sensitive to change across time. The SomaSignalTM Mid‐Life Dementia Risk Test is a blood‐based, protein‐only prognostic model developed using SomaScan® Assay v4.0 (measuring ∼5,000 proteins) combined with machine learning methods to predict 20‐year risk for dementia in individuals aged 49 years and older. However, shorter term risk stratification for dementia may better enable early detection of emerging changes in cognition, enrich clinical trial enrollment for novel interventions, and eventually improve precision medicine prescribing of therapeutics. Thus, the 20‐year dementia risk test was re‐calibrated to maximize performance of 5‐year prediction in an older population.MethodThe 25‐protein Mid‐Life Dementia Risk model was re‐calibrated to predict 5‐year risk for a dementia diagnosis in adults aged 65 and older. We utilized plasma samples from ARIC visit 5 (n = 4985; median age 75 years) for the re‐calibration, which included a total of 391 total incident dementia diagnoses occurring within 5 years of blood draw. Re‐calibrated models were assessed in a training dataset consisting of 70% of the ARIC visit 5 data to identify the optimal 5‐year risk model. The final model was tested for robustness in a 15% holdout sample and validated independently in the remaining 15% samples.ResultThe AUC of the re‐calibrated 5‐Year Dementia Risk model was equal to 0.778, 0.735, and 0.776, in training, verification, and validation datasets, respectively. Individuals were stratified by relative risk into Low‐, Medium‐Low‐, Medium‐High‐, and High‐risk bins, with a 5‐year dementia diagnosis rate of 1.510% in the Low‐risk bin vs 20.337% in the High‐risk bin. The performance of the proteomic model was superior to that of APOE genotype or age in predicting 5‐year dementia risk as evaluated by AUC and dynamic range.ConclusionThe 20‐Year Dementia Risk Test was successfully re‐calibrated to predict 5‐year dementia risk in individuals aged 65 years and older with more than a 13‐fold dynamic range for risk stratification. The proteomics‐based 5‐Year Dementia Risk Test outperforms leading risk factors for dementia, including APOE genotype and age.
Constrained Decoupled Dictionary Learning of Task fMRI data
Authors: Pillai Sreekrishna R. , Carmichael Owen T. , Bazzano Lydia 
Published: December 2023

AbstractBackgroundDictionary learning techniques have the potential to efficiently detect functional connectivity impairments in distributed brain networks associated with Alzheimer’s Disease (AD) when applied to task functional magnetic resonance imaging (tfMRI) data. However, traditional methods are constrained in what brain networks they can identify due to the statistical independence assumptions they make, and they do not leverage the structure of the tfMRI task when identifying networks. We used a new sparse dictionary learning technique to identify brain functional network correlates of cardiometabolic risk variables in a community‐based cohort.MethodThe Bogalusa Heart Study (BHS) is community‐based cohort study of atherosclerosis and risk factors for cardiovascular disease. fMRI data was collected from 100 participants of BHS during performance of a Stroop task. Spatially concatenated tfMRI data was factorized into a group‐wise temporal dictionary matrix and a set of scan‐level spatial patterns while biasing a subset of learned temporal patterns to be paradigm related. Scan‐level spatial patterns obtained as a result were aggregated and factorized to derive a group‐level spatial dictionary matrix and sparse loading coefficients. The sparse loading coefficients obtained from this Constrained Decoupled Dictionary Learning (CDDL) method were used as descriptive biomarkers, the relevance of which was established by using them to predict cardiometabolic variables including fasting glucose level, homeostatic model assessment for insulin resistance (HOMA‐IR) index and fasting insulin level using support vector regression and a leave‐one out cross‐validation. The performance of the algorithm was calculated in terms of Mean Absolute Percentage Error (MAPE) between actual and predicted cardiometabolic variable valuesResultThe SVM regressor was able to predict the cardiometabolic variables with low MAPE. The prediction of glucose values achieved the least MAPE for all kernel types (Table 1).ConclusionCombining prior knowledge, decoupling of spatial and temporal patterns, and high‐dimensional regression, we generated brain functional network patterns from real‐world tfMRI data that associated with known cardiometabolic indicators of brain health. These brain functional network patterns thus have the potential to serve as indicators of brain health.
Alzheimer’s Disease Biomarkers: Roles of Type 2 Diabetes from the HABS‐HD Study
Authors: Yu Fang , Pituch Keenan A , Maxfield Molly , Basena Elsa , Geda Yonas E. , Pruzin Jeremy J. , Coon David W. , Shaibi Gabriel Q ,   Health and Aging Brain Study: Health Disparities (HABS‐HD) Study Team
Published: December 2023

AbstractBackgroundAlzheimer’s disease (AD) disproportionately affects Mexican Americans, however, reasons underlying this health disparity remain unknown. Type 2 diabetes (T2D) is a risk factor for AD and may contribute to AD pathogenesis. The purpose of this study was to examine the associations between T2D and AD blood biomarkers among Mexican Americans and non‐Hispanic Whites.MethodsThis study analyzed baseline data from the Health and Aging Brain Study: Health Disparities (HABS‐HD) that investigated AD differences among Mexican Americans and non‐Hispanic White. HABS‐AD participants were excluded from this study if they had missing data or were outliers (z‐scores >|4|) on a given AD biomarker (N = 1,552 for Aβ42/40 ratio, 1,570 for t‐tau, and 1,553 for NfL). AD biomarkers included plasma Aβ42/42 ratio, total tau (t‐tau), and neurofilament light (NfL) analyzed using Simoa. Predictors were blood glucose, HbA1c, and T2D diagnosis. Data were analyzed with regression analyses controlling for covariates (e.g., demographics, smoking, BMI, health status, diseases, cognition) and treating missing predictor data using Bayesian MCMC estimation.ResultsMexican Americans differed significantly from non‐Hispanic Whites in age (66.6±8.7 vs. 69.5±8.6), sex (64.9% female vs. 55.1%), education (9.5±4.6 vs. 15.6±2.5), blood glucose (113.5±36.6 vs. 99.2±17.0), HbA1c (6.33±1.4 vs. 5.51±0.6), T2D diagnosis (35.3% vs. 11.1%), Aβ42/40 ratio (.051±.012 vs. .047±.011), t‐tau (2.56±.95 vs. 2.33±.90), and NfL (16.3±9.5 vs. 20.3±10.3). The models with the covariates and predictors accounted for 6% (p<.001), 15% (p<.001), and 36% (p<.001) of the variation in Aβ42/40 ratio, t‐tau, and NfL, respectively. Blood glucose, HbA1c, and T2D diagnosis were not related to Aβ42/40 ratio and t‐tau but explained 3.7% of the variation in NfL (p<.001). Among non‐Hispanic Whites, blood glucose, HbA1c, and T2D diagnosis were negatively (b = ‐0.09, p<.01, β = ‐0.26), not (b = 0.34, p = .71, β = 0.04), and positively (b = 3.32, p<.01, β = 0.33) associated with NfL, respectively. In contrast, blood glucose and T2D diagnosis were not, while HbA1c was positively (b = 2.31, p<.001, β = 0.26), associated with NfL among Mexican Americans.ConclusionBlood glucose, HbA1c, and T2D may contribute to differences in NfL levels, but not Aβ42/40 ratio and t‐tau, in an ethnicity‐specific manner. Future studies are needed to corroborate our findings in longitudinal cohorts.
Investigating the role of Donepezil in promoting Oligodendrocyte precursor cell (OPC) differentiation and Therapeutic Potential in Alzheimer’s Disease (AD)
Authors: Ismail Youssef Ahmed , Walid Mohammad 
Published: December 2023

AbstractBackgroundStatistical analysis of myelin basic protein (MBP) cells generated from Neural progenitor cell (NPC)‐derived Oligodendrocyte precursor cells (OPCs) treated with various AChEIs, including donepezil, huperzine A, rivastigmine and tacrine, revealed that only donepezil is capable of facilitating OPC‐to‐OL formation, indicating that donepezil’s effect in promoting OPC differentiation is not dependent on the inhibition of AChE. So, it can be possible that OPC‐to‐OL formation is why donepezil is considered leading in Alzheimer’s disease (AD) treatment.MethodTrial will include transgenic rat line Tg6590 that expresses human APP with the Swedish mutation driven by the ubiquitin promoter that doesn’t develop extracellular beta‐amyloid pathology before 15 months at least. Controlling their genome influence, the cognitive characteristics of mice can be related to neurobiological characteristics only. Excluding a standard (S), group of control animals was subjected to a CPZ‐free diet; rat (+MBP) will be injected with OPCs, and rat (‐MBP) will be supplemented with 0.6% cuprizone (CPZ) for 2 weeks, which facilitates demyelination. This study enables us to observe the myelination effect on its behavioral impairment (n = 3). Luxol fast blue (LFB) test or MBP tracking will be held monthly to observe OPCs‐to‐OL process. It was reported that Tg6590 rats display learning and memory deficits in the Morris water maze at the age of 9 months and altered spontaneous behavior measured in open‐field. So, with continuous behavioral observations, by procedure for a redundant place/cued version of Morris water maze task, memory‐learning assessment (MLA) will depend upon duration it takes to observe obvious behavioral impairment.ResultThis clinical trial is now under process and it is set to start by late 2024.ConclusionOPCs implantation may lead to axonal adaptation to physical stress with less beta‐amyloid and may also maintain the myelination density in CNS, especially in hippocampal‐neocortical neural connections, which can be therapeutically efficient for memory‐learning deficits.
Contributors to sleep disturbances in caregivers and care recipients with dementia
Authors: Manning Carol A , Youngkin Anna E , Quigg Mark S 
Published: December 2023

AbstractBackgroundSleep disturbances in Alzheimer’s disease impact people with dementia (PWD) and caregivers (CGS) who have primary responsibility for care provision. However, it is unknown which aspects of dementia including cognitive decline and behavioral disturbance contribute most to sleep disturbances in patients and caregivers. This pilot study aims to discover what contributes most to sleep deficits, and whether these factors are consistent across both PWD and CGS.MethodPatients: Six dyads with PWD and their primary CGS. Cognitive/behavioral variables: the Montreal Cognitive Assessment (MoCA) (PWD) and the Neuropsychiatric Inventory Questionnaire (NPI‐Q) completed by CGS. Polysomnography: recorded and scored for 1 night for each dyad member separately. Actigraphy: Wrist actigraphy recorded for 14 days in both members of the dyad divided into fixed rest (2200‐0600) and activity (0600‐2200) periods. Sleep variables: total sleep time (TST), sleep onset latency (SOL), nighttime activity as measured by actigraphy.ResultPreliminary results indicate that severity of cognitive dysfunction measured by the MoCA correlates with sleep time (CG r = 0.6224, PWD r = 0.5421). However, presence of neuropsychiatric symptoms and caregiver distress as measured by the NPIQ correlate with sleep onset latency (CG r = 0.9432*, PWD r = 0.7819) and nighttime activity in both CGs and PWD (CG r = 0.8467, PWD r = 0.8708). * = p<0.05.ConclusionThis pilot study of six PWD/CGS dyads examines the relationship between cognition, behavioral disturbance, CGS response to the behavioral disturbance, and sleep. This data indicates that sleep disturbances in PWD and their CGs cannot be explained exclusively by worsening cognitive function and likely have stronger dependence on the neuropsychiatric well‐being of the PWD and CGS emotional response. This dyadic model is unique in that it looks at the interdependence of the PWD/CGS dyad using both objective measures of sleep, cognition, and behavioral disturbance as well as subjective CGS stress. Data from additional dyads is currently being collected to increase the sample size along with the inclusion of additional variables in order to increase understanding of the relationship between PWD characteristics, caregiver burden and sleep disturbances.