1,720,958 research outputs found
Imputation-Based Variable Selection Method for Block-Wise Missing Data When Integrating Multiple Longitudinal Studies
No full textWhen integrating data from multiple sources, a common challenge is block-wise missing. Most existing methods address this issue only in cross-sectional studies. In this paper, we propose a method for variable selection when combining datasets from multiple sources in longitudinal studies. To account for block-wise missing in covariates, we impute the missing values multiple times based on combinations of samples from different missing pattern and predictors from different data sources. We then use these imputed data to construct estimating equations, and aggregate the information across subjects and sources with the generalized method of moments. We employ the smoothly clipped absolute deviation penalty in variable selection and use the extended Bayesian Information Criterion criteria for tuning parameter selection. We establish the asymptotic properties of the proposed estimator, and demonstrate the superior performance of the proposed method through numerical experiments. Furthermore, we apply the proposed method in the Alzheimer’s Disease Neuroimaging Initiative study to identify sensitive early-stage biomarkers of Alzheimer’s Disease, which is crucial for early disease detection and personalized treatment
Escalation of Tau Accumulation after a Traumatic Brain Injury: Findings from Positron Emission Tomography
No full textTraumatic brain injury (TBI) has come to be recognized as a risk factor for Alzheimer’s disease (AD), with poorly understood underlying mechanisms. We hypothesized that a history of TBI would be associated with greater tau deposition in elders with high-risk for dementia. A Groups of 20 participants with self-reported history of TBI and 100 without any such history were scanned using [18F]-AV1451 positron emission tomography as part of the Alzheimer’s Disease Neuroimaging Initiative (ADNI). Scans were stratified into four groups according to TBI history, and by clinical dementia rating scores into cognitively normal (CDR = 0) and those showing cognitive decline (CDR ≥ 0.5). We pursued voxel-based group comparison of [18F]-AV1451 uptake to identify the effect of TBI history on brain tau deposition, and for voxel-wise correlation analyses between [18F]-AV1451 uptake and different neuropsychological measures and cerebrospinal fluid (CSF) biomarkers. Compared to the TBI-/CDR ≥ 0.5 group, the TBI+/CDR ≥ 0.5 group showed increased tau deposition in the temporal pole, hippocampus, fusiform gyrus, and inferior and middle temporal gyri. Furthermore, the extent of tau deposition in the brain of those with TBI history positively correlated with the extent of cognitive decline, CSF-tau, and CSF-amyloid. This might suggest TBI to increase the risk for tauopathies and Alzheimer’s disease later in life
Distinguishing Early from Late Mild Cognitive Impairment Using Magnetic Resonance Free-Water Diffusion Tensor Imaging
No full textMild Cognitive Impairment (MCI) is a transitional stage between normal aging and Alzheimer’s disease. Differentiating early MCI (EMCI) from late MCI (LMCI) is crucial for early diagnosis and intervention. This study used free-water diffusion tensor imaging (fw-DTI) to investigate white matter differences and voxel-based correlations with Mini–Mental State Examination (MMSE) scores. Data from the Alzheimer’s Disease Neuroimaging Initiative included 476 healthy controls (CN), 137 EMCI participants, and 62 LMCI participants. Significant MMSE differences were found between the CN and MCI groups, but not between EMCI and LMCI. However, distinct white matter changes were observed: LMCI showed a higher f-index and lower fw-fractional anisotropy (fw-FA) compared to EMCI in several white matter regions. These findings indicate specific white matter tracts involved in MCI progression. Voxel-based correlations between fw-DTI metrics and MMSE scores further supported these results. In conclusion, this study provides crucial insights into white matter changes associated with EMCI and LMCI, offering significant implications for future research and clinical practice
Association of a Total Cholesterol Polygenic Score with Cholesterol Levels and Pathological Biomarkers across the Alzheimer’s Disease Spectrum
No full textMidlife hypercholesterolemia is a well-known risk factor for sporadic Alzheimer’s disease (AD), and like AD, it is highly influenced by genetics with heritability estimates of 32–63%. We thus hypothesized that genetics underlying peripheral blood total cholesterol (TC) levels could influence the risk of developing AD. We created a weighted polygenic score (TC-PGS) using summary data from a meta-analysis of TC genome-wide association studies for evaluation in three independent AD-related cohorts spanning pre-clinical, clinical, and pathophysiologically proved AD. APOE-ε4 variant was purposely included in the analysis as it represents an already well-established genetic risk factor for both AD and circulating TC. We could vastly improve the performance of the score when considering p-value thresholds for inclusion in the score, sex, and statin use. This optimized score (p-value threshold of 1 × 10−6 for inclusion in the score) explained 18.2% of the variance in TC levels in statin free females compared to 6.9% in the entire sample and improved prediction of hypercholesterolemia (receiver operator characteristics analysis revealed area under the curve increase from 70.8% to 80.5%). The TC-PGS was further evaluated for association with AD risk and pathology. We found no association between the TC-PGS and either of the AD hallmark pathologies, assessed by cerebrospinal fluid levels of Aβ-42, p-Tau, and t-Tau, and 18F-NAV4694 and 18F-AV-1451 positron emission tomography. Similarly, we found no association with the risk of developing amyloid pathology or becoming cognitively impaired in individuals with amyloid pathology
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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