bluuebunny/crossref_metadata_2025_split huggingface dataset:
Age‐related association between white matter integrity and cerebral blood flow in white matter
Authors: Jekel Ciara , Kim Donghoon , Hughes Tim M. , Lockhart Samuel N. , Whitlow Christopher T. , Craft Suzanne , Baker Laura D. , Okonmah‐Obazee Stephanie , Bobinski Matthew , Jung Youngkyoo 
Published: February 2022

AbstractBackgroundAlzheimer’s disease (AD) has a long preclinical phase that is often preceded by reduced white matter (WM) integrity; further, impaired cerebrovascular function is associated with AD biomarkers. However, the intersection of WM structure and cerebrovascular function in the risk and progression of Alzheimer’s disease is unclear. We examined the relationship between WM structure and cerebrovascular function in younger and older adults at risk for AD.MethodParticipants enrolled in the Wake Forest Alzheimer’s Disease Research Center Clinical Core underwent: 3T MRI scan including neurite orientation dispersion and density imaging (NODDI) and arterial spin labeling (ASL), clinical exams, cognitive testing, and adjudication. Intra‐cellular volume fraction (ICVF) and cerebral blood flow (CBF) were obtained from NODDI and ASL, respectively. Multivariable linear regression analyses were performed to investigate the relationship between ICVF and CBF in 48 WM regions (JHU ICBM‐DTI‐81 atlas). Analyses were performed separately on participants grouped by age (median split at ≥71 years) and adjusted for covariates: sex, race, and cognition status, and grouped by cognitive status and adjusted for covariates: sex, race, and age. The Benjamini & Hochberg false discovery rate method was used to test multiple hypothesis across ROIs.Result330 participants completed MRI sequences for WM structure and perfusion (mean age: 70.3±8 yrs.; M/F: 105/225; 283 White, 47 Black or African American; 198 cognitively normal, 132 mild cognitive impairment (MCI)). The older group had lower mean ICVF and mean WM CBF (0.70±0.05; 18.9±3) than the younger group (0.73±0.04; 19.7±3). In the older group, mean ICVF was positively related to mean WM CBF (p<0.01). In older participants (≥71) there were eight regions where ICVF and CBF were positively related (corrected p<0.05). In younger participants (<71) there was one region where ICVF and CBF were positively related (fornix column and body; corrected p<0.05). When grouped by cognitive status (normal/MCI), no association was found between mean ICVF and mean WM CBF.ConclusionGenerally, reduced integrity in WM structure is associated with reduced CBF. This association appears related to age, not cognitive status. Differences in the associated regions by age suggest potential effects of brain aging on WM structure and CBF.
Evaluating participant and coordinator satisfaction with telephone assessments
Authors: Pun Kelly , Sewell Margaret , Neugroschl Judith A , Zhu Carolyn W , Zeng Xiaoyi , Greenberg Jonathan , Velasco Nelly , Sheppard Faye , Tocco Carly , Evans Kirsten , Ardolino Allison , Meuser Caroline , Kinsella Michael T , Li Clara , Loizos Maria , Grossman Hillel , Sano Mary 
Published: February 2022

AbstractBackgroundIn response to the COVID‐19 pandemic, the Alzheimer’s Disease Research Center (ADRC) at the Icahn School of Medicine at Mount Sinai began conducting evaluations for the National Alzheimer’s Coordinating Center Uniform Data Set (NACC UDS) by telephone in March 2020. The ADRC designed a survey to evaluate participant and research coordinator satisfaction with telephone evaluations.MethodFollowing UDS evaluations, participants rated their satisfaction on 5 items: voice quality on telephone, respect for privacy, degree of comfort using the telephone, and confidence that the information collected was accurate. Coordinators were asked to gauge their satisfaction on similar items. To calculate satisfaction scores, responses were assigned values: “Very” = 3, “Fairly” = 2, and “Not at all” = 1. Maximum satisfaction score was 15 for participants and 18 for coordinators.ResultData was available for 130 participants evaluated by telephone between March 2020 and January 2021. Of these, 68.5% were female, 53.7% were white, with an average age of 76.4 and 16 years of education. 74% of participants had a Global Clinical Dementia Rating (CDR) score of 0; 22% CDR 0.5; 4% CDR 1. Participants with CDR >1 were evaluated by caregiver interviews without testing, and those with CDR=1 were offered testing at the discretion of their family and examiners. Average total satisfaction rating was 14.2/15 for participants and 16.8/18 for coordinators. 98% of participants felt their privacy was “very” respected (mean 2.98/3). When looking at global CDR scores, 89.6% of participants with CDR=0 and 88.2% with CDR ≥0.5 were “very” confident in the accuracy of the information collected. In contrast, coordinators were “very” confident in the accuracy of their evaluation 84.4% of the time when participants had a CDR=0 and 67.7% of the time when participants had a CDR ≥0.5.ConclusionOverall satisfaction with telephone evaluations was high, but participant and coordinator confidence in the accuracy of assessments varied, with coordinator satisfaction lower for more cognitively impaired participants. Future work will analyze satisfaction with ongoing remote assessments and evaluate the impact of additional demographic and diagnostic variables.
Gait changes among older adults during a virtual wayfinding task: The role of spatial disorientation and heart rate variability
Authors: Amaefule Chimezie O , Lüdtke Stefan , Kirste Thomas , Teipel Stefan J 
Published: February 2022

AbstractBackgroundAging has been associated with decline in cognitive and motor performance, often expressed in dual‐task walking situations, such as wayfinding. A major barrier to successful wayfinding is spatial disorientation, occurring mostly at intersections. Although gait changes have been observed in various walking conditions, little is known about the effect of spatial disorientation on gait in wayfinding among older adults.Method24 participants (16 female) were measured in 3 conditions: 6 young controls (mean age = 23.50 years, SD = 0.54), 9 old controls (mean age = 68.77 years, SD = 2.72; mean MMSE = 28.85, SD = 0.89) and 8 old experimental (mean age = 71.87 years, SD = 5.38; mean MMSE = 29.14, SD = 0.80). Participants performed a wayfinding task consisting of about 14 decision points (i.e. intersections) within a virtual environment (VE), on a self‐paced treadmill equipped with a marker‐based optical motion‐capture system. The VE was held constant for the controls, and manipulated (e.g. moved landmarks) for the experimental participants. Heart rate was continuously monitored as a measure of psychophysiological response. Statistical analyses using Linear Mixed Effects Models and t‐tests, focused on hypothesis‐driven outcome measures extracted from decision points.ResultInitial evaluation of the outcome measures show considerable effects of the disorientation intervention on gait; both the old control (constant VE) and experimental (manipulated VE) participants showed some variation in walking speed during instances of disorientation. This effect was, however, more pronounced, t(39) = ‐3.66, p<.001, for the old experimental condition participants (Figure 1).ConclusionUnderstanding underlying motion and psychophysiological signatures of spatial disorientation among older adults is a necessary first step, towards developing efficient situation‐aware assistive devices necessary for independent mobility. Initial findings show increased gait variability during instances of disorientation. The association of the disorientation effect with psychophysiological response is also being investigated. Further results will be presented by July 2021.
Strategies for activity maintenance in patient and family care and clinical trial adherence of GNA social plan in context of COVID‐19 health emergency
Authors: Andrade‐Villegas Angela M , Aguillon David , Gómez Manuela , Gómez‐Henck Clara , Zuluaga Maria , Rassi Sofia , Ramos Claudia , Madrigal Claudia , Uribe Claramonika , Saldarriaga Amanda , Alzate Diana , Ruiz Alejandra , Giraldo Andrea , Giraldo‐Chica Margarita , Reiman Eric M , Sink Kaycee M , Rios‐Romenets Silvia , Madrigal Lucia , Lopera Francisco 
Published: February 2022

AbstractBackgroundThe current pandemic COVID‐19 caused by SARS‐CoV2 has become a public health challenge, causing difficulty in patient care and follow up of people with cognitive impairment due to Alzheimer's disease. This situation motivated changes and adjustments to the Group of Neurosciences of Antioquia’s (GNA) Social Plan to guarantee effective continuity in patient care, family follow‐up, community interventions and adherence to the Alzheimer’s Prevention Initiative (API) Colombia clinical trial. This was an opportunity to innovate, create, reinvent and expand forms of care and intervention during confinement and pandemic to promote access through virtual media and the well‐being of beneficiaries.MethodsThe Social Plan program involves free access to basic care supplies for patients, home‐visits, support groups, cognitive stimulation groups and virtual community outreach activities like workshops for caregivers/interested public, Alzheimer's Day Commemoration “Cuidarme – Cuidarte” event (with available recorded resources), symposiums for caregivers, and informative meetings with participants of the API Colombia clinical trial.ResultsIn the period of mandatory preventive confinement, 30 families obtained diapers, 23 families received prescription drugs not provided by health maintenance organizations (HMO) and 48 families received groceries. A total of 32 home‐visits were made: 7 in rural areas and 25 in urban areas. At the end of the mandatory preventive confinement, outpatient medical consults were resumed, no participants withdrew from the trial during this period. Thirty‐six people with MCI or dementia participated in virtual cognitive stimulation activities. Caregiver remote workshops held in the first semester of 2020 had a total attendance of 80 people, and events held in the second semester, such as the Commemoration of Alzheimer's Day and the Symposium for Caregivers, had a total attendance of 1,665 people and 1,000 people respectively.ConclusionGNA’s Social Plan and the amended which includes strategies of social support, knowledge and patient/caregiver empowerment strengthened the interaction between the community and GNA and likely favorably influenced adherence and retention in the API Colombia clinical trial in the face of challenges from the global pandemic.
Disentangling disease heterogeneity from neuroimaging data via adaptive distribution modeling–based collaborative clustering
Authors: Liu Hangfan , Grothe Michel J. , Rashid Tanweer , Labrador‐Espinosa Miguel , Toledo Jon B. , Habes Mohamad 
Published: February 2022

AbstractBackgroundNeurodegenerative diseases, including Parkinson’s disease (PD), are clinically heterogeneous, with distinct subtypes encompassed within the same clinical diagnosis. Heterogeneity in brain diseases makes it challenging to recruit ideal patients into trials for suitable treatment or develop markers that capture the disease’s signals. Data‐driven clustering coupled with high dimensional neuroimaging data could further our understanding of heterogeneous disease biology and assigning specific patients groups to individualized treatments.MethodWe propose an Adaptive Distribution based COllaborative Clustering (ADCoC) method, which simultaneously clusters subjects and features via nonnegative matrix tri‐factorization. For denoising, we further introduce adaptive regularization based on coefficient distribution modeling. Unlike related sparsity techniques [1], we form the distributions using the data of interest to better fit the coefficients. We studied structural MRI data from 170 PD patients and 77 healthy controls enrolled in the Parkinson Progression Markers Initiative (PPMI). ADCoC partitioned the patients into 2 clusters. We compared the distribution of ICV normalized grey matter volumes in different regions between the two patient clusters and the healthy control group by student’s t‐test. Then we analyzed neuropsychological test data to compare the cognitive performance of the two patient clusters and the control group.ResultTest statistic values of regions with FDR corrected p‐values smaller than 0.05 are plotted in Figure 1. Comparisons with the healthy control group show that PD cluster PD‐Post (54.7% of the PD samples) is characterized by a posterior cortical‐medial temporal atrophy pattern with worse cognition compared to PD cluster PD‐Front which had atrophy circumscribed to the frontal lobe areas. Analysis of neuropsychological test data further demonstrates that these MRI‐defined patient subtypes also show differences in clinical presentation, where PD‐Post show statistically significant lower cognitive performance compared to PD‐Front (Montreal Cognitive Assessment [MoCA] scores: 27.1 ± 2.4 [PD‐Post] vs 27.9 ± 1.7 [PD‐Front], p = 0.014).ConclusionWhen applied to a clinical dataset of MRI data from PD patients, ADCoC identified two stable and highly reproducible patient clusters characterized by frontal and posterior cortical‐medial temporal atrophy patterns. References: [1] H. Liu et al., "Adaptive sparsity regularization based collaborative clustering for cancer prognosis," MICCAI'19.
Microglia activation predicts tau positivity beyond Aβ in Alzheimer’s disease
Authors: Ottoy Julie , Bezgin Gleb , Savard Mélissa , Mathotaarachchi Sulantha , Pascoal Tharick A. , Chamoun Mira , Soucy Jean‐Paul , Gauthier Serge , Rosa‐Neto Pedro 
Published: February 2022

AbstractBackgroundDeposition of amyloid‐beta (Aβ) plaques and hyperphosphorylated tau are known hallmarks of Alzheimer’s disease (AD). In addition, neuroinflammation or microglia activation plays a role in AD pathophysiology and may be a potential driver of abnormal tau deposition. This study demonstrated the important brain regions where microglia activation, in addition to Aβ, is driving tau positivity in AD.Method120 participants from the TRIAD cohort underwent 18F‐AZD4694 amyloid‐PET, 18F‐MK620 tau‐PET, and 11C‐PBR28 neuroinflammation‐PET. All images were normalized to the ADNI template and quantified as SUVR in 35 regions‐of‐interest using cerebellar gray as the reference region. ANCOVA was used to assess the differences in levels of microglia activation between tau‐positive (T+; n=38) vs. tau‐negative (T‐; n=82), corrected for age, sex, APOE‐e4, education, and global Aβ. Tau status was based on both visual rating with elevated uptake in Braak1and2 and quantitative cut‐off of 1.22. In addition, step‐wise logistic regression was conducted to predict T+ in three steps: 1) the covariates, i.e. age, sex, APOEε4, and education, 2) covariates + global Aβ, and 3) covariates + global Aβ + activated microglia in each of the 35 ROIs, corrected for multiple comparisons using FDR. Our prediction model was trained based on a randomly selected 70%/30% training/test set. In order to investigate the stability of our model, this procedure was repeated 500 times.ResultLevels of microglia activation were significantly increased in T+ compared to T‐ in the posterior cingulate (p=0.0001), middle (p=0.02) and inferior (p=0.0005) temporal, fusiform (p=0.0004), and orbitofrontal cortex (p=0.005). Based on logistic regression and a likelihood‐ratio test between each step, we found that the ‘covariates + global Aβ model’ performed significantly better in predicting T+ than the ‘covariates‐only’ model (χ2(1)=72.64, p<0.0001). In the 3‐step model, the addition of activated microglia showed a significant improvement of the model’s performance to predict T+, particularly the activated microglia in the hippocampus (p=0.001), middle (p=0.006) and inferior (p=0.001) temporal, and fusiform (p=0.001) cortex. Receiver operating characteristic curves (ROC) and AUCs are shown in Fig 1.ConclusionOur study demonstrated that activated microglia in the Braak2 to Braak4 regions play an important role in predicting tau positivity in addition to Aβ.
Discovering genetic biomarkers for Alzheimer’s disease using 2D‐CNN and GWAS
Authors: Pan Dan , Rong Huabin , Zeng An , Huang Yin , Jia Longfei , Song Xiaowei 
Published: February 2022

AbstractBackgroundTo identify candidate neuroimaging and genetic biomarkers for Alzheimer’s Disease (AD) and other brain diseases, especially for little‐known brain disorders, in a data‐driven way, we advocate an approach which incorporates an adaptive classifier ensemble model by combining Convolutional Neural Network (CNN) and Ensemble Learning with Genetic Algorithm (GA), i.e., the CNN‐EL‐GA method, into Genome‐Wide Association Studies (GWAS).MethodIn the CNN‐EL‐GA method, a large number of base classifiers, i.e., CNN models, were trained utilizing a set of sagittal, coronal, or transversal magnetic resonance imaging slices, and the CNN models with strong discriminability were then selected and integrated into a single classifier ensemble with the GA for classifying AD. While the generalization capability of the acquired classifier ensemble was maximized, the intersection points were decided by the most discriminative slices among the sagittal, coronal, and transversal slice sets. The gray matter volumes of the top ten discriminative brain regions which contained the most intersection points were utilized to carry out GWAS together with the genotypic data. The pipeline of the proposed approach incorporating the CNN‐EL‐GA method into GWAS for discovering candidate genetic biomarkers of AD is shown in Figure 1.ResultSix genes of PCDH11X/Y, TPTE2, LOC107985902, MUC16 and LINC01621 as well as Single Nucleotide Polymorphisms, e.g., rs36088804, rs34640393, rs2451078, rs10496214, rs17016520, rs2591597, rs9352767 and rs5941380, were identified.ConclusionThis approach overcomes the limitations associated with subjective factors while adaptively achieving more robust and effective candidate biomarkers in a data‐driven way. The approach is promising to advance the discovery of effective candidate genetic biomarkers for brain disorders.
White matter integrity is associated with self‐awareness of financial decision‐making in cognitively healthy older adults
Authors: Sunderaraman Preeti , Gazes Yunglin , Ortiz Gema , Chapman Silvia , Joyce Jillian L. , Langfield Christopher , Mensing Ashley , Stern Yaakov , Cosentino Stephanie 
Published: February 2022

AbstractBackgroundReduced awareness of one’s financial decision‐making abilities (financial awareness) can result in costly financial mistakes (e.g., forgetting to pay credit card dues) and increase one’s vulnerability to financial exploitation (e.g., getting scammed). In cognitively healthy older adults, thinner right medial temporal cortex is associated with overconfidence in one’s financial decision‐making abilities. However, it is important to examine other neuroimaging metrics to create a comprehensive picture of the links between brain and financial awareness in healthy older adults. In the current study, we examined the white matter correlates of financial awareness and hypothesized that the tracts connecting the right temporal‐frontal regions would be most strongly correlated with financial awareness.MethodDesign ‐ Cross‐sectional, prospective study. Setting ‐ Community‐based. Participants: 44 individuals were included with mean age=68.43 years (SD=5.1), mean education=15.88 (SD=2.41), 60% = women, 67% = White, 30% = Black and 3% = other races, and 95% = non‐Hispanics. Measures: Awareness Metrics – Financial awareness was measured by integrating metacognitive ratings into the Objective Financial Competency Assessment Inventory. Before each item, we obtained confidence ratings regarding performance on that item. Level of awareness was operationalized via a calibration score reflecting the difference between average performance and average confidence, reflecting the extent to which individuals were over‐ or under‐confident. Mean Diffusivity – Data were processed with Tracts Constrained by Underlying Anatomy toolbox distributed as part of the FreeSurfer library (v5.3) which produced averages of mean diffusivity for 18 white matter tracts. Lower mean diffusivity values indicated higher white matter integrity.ResultThe right superior longitudinal fasciculus–temporal (r = 0.437, p = 0.003) and parietal (r = 0.433, p = 0.003) bundles had the strongest correlations with calibration scores such that higher (i.e., worse) diffusivity was associated with values reflecting over‐confidence.ConclusionOur findings converge with the growing literature on the unique role of the right hemisphere temporal connections in supporting financial awareness. We find an equally important role for right parietal‐frontal connections in financial awareness. Our findings are in line with studies on financial exploitation in which the right parietal and temporal pathways were found to be involved in scam susceptibility.
A novel MRI approach for evaluation of microstructural neurodegeneration in early Alzheimer disease
Authors: Kothapalli Satya V.V.N. , Benzinger Tammie L.S. , Aschenbrenner Andrew J. , Perrin Richard J. , Hildebolt Charles F. , Goyal Manu S. , Fagan Anne M. , Raichle Marcus E. , Gordon Brian A. , Morris John C. , Yablonskiy Dmitriy A. 
Published: February 2022

AbstractBackgroundCurrently, brain tissue atrophy serves as in vivo structural MRI biomarker of neurodegeneration in Alzheimer Disease (AD). However, postmortem histopathological studies show that neuronal loss in AD exceeds volumetric loss of tissue and that AD‐related memory loss begins when neurons are lost. Hence, in vivo detection of neurodegeneration preceding detectable atrophy is essential for early AD diagnosis.MethodOur innovative approach to assessing neuronal damage in vivo is based on (a) quantitative Gradient Recalled Echo (qGRE) MRI technique and (b) genetically‐informed relationships between qGRE metrics and major components of brain tissue cellular structure (neurons/neurites and glia) that were obtained using gene expression profiles across the human brain provided by the Allen Human Brain Atlas. Seventy participants were recruited from the Knight Alzheimer Disease Research Center, representing three groups: Healthy controls [Clinical Dementia Rating® (CDR®)=0, amyloid β (Aβ)‐negative), n=34] HC; Preclinical AD (CDR=0, Aβ‐positive, n=19), PC; and mild AD (CDR=0.5 or 1, Aβ‐positive, n=17), AD.ResultPreliminary data show that qGRE identified new biomarkers in AD brain characterizing tissues with significantly lower (termed Dark Matter) and relatively preserved (termed Viable Tissue) concentrations of neurons. The fraction of Dark Matter showed clinically important and significant differences between HC and PC groups in hippocampus, middle temporal, fusiform, postcentral, and inferior parietal brain regions. However, no HC vs. PC group difference was detected by the volumetric measurements (Figure 1). Further, measurements of the Dark Matter fraction in the hippocampus showed strong associations with Cerebrospinal fluid (CSF) amyloid Aβ42 (r=‐0.52), CSF ptau (r=0.60), 18F‐AV1415‐PET tau imaging (r=0.60), and PiB‐PET amyloid imaging (r=0.60). These associations were significantly stronger compared with volumetric measurements: CSF amyloid Aβ42 (r=0.18), CSF ptau (r=‐0.24), PET tau imaging (r=‐0.39), and PiB‐PET amyloid imaging (r=‐0.17)). Importantly, the Dark Matter fraction had a significant inter‐regional association (r=0.87) with neuronal count in the hippocampal subfields obtained from histopathological study of one participant who underwent in vivo qGRE 14 months prior to expiration (Figure 2).ConclusionqGRE‐based measurements identify the microstructural changes in early AD‐related neurodegeneration that are not recognized by structural MRI atrophy measurements, therefore providing new biomarkers for early AD detection.