MétaCan
Menu
← Back to cohort
Record W1984220317 · doi:10.1016/j.jalz.2013.04.477

O5–02–03: Regional distribution of brain fibrillar amyloid deposition as a function of CSF beta‐amyloid 1–42 and biomarkers of neurodegeneration

2013· article· en· W1984220317 on OpenAlexaff
Laksanun Cheewakriengkrai, Jared Rowley, Sara Mohades, Thomas Beaudry, Antoine Leuzy, Eduardo R. Zimmer, Vladimir Fonov, Serge Gauthier, Pedro Rosa‐Neto

Bibliographic record

VenueAlzheimer s & Dementia · 2013
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsMcGill University
Fundersnot available
KeywordsPrecuneusAmyloid (mycology)Pittsburgh compound BStandardized uptake valueWhite matterPathologyNeurodegenerationAmyloid betaAlzheimer's diseaseNuclear medicineMedicineNeuroscienceInternal medicinePositron emission tomographyPsychologyMagnetic resonance imagingDiseaseRadiologyCognition

Abstract

fetched live from OpenAlex

Fibrillar amyloid deposition is one of the main features of Alzheimer's disease (AD) and occurs in various cortical regions. Although age and APOE4 status contribute to global amyloidosis, factors involved on regional deposition of fibrillary amyloid are currently unknown. Here, we described associations between regional fibrillar amyloid deposition (measured with [11 C]PIB or [18 F]florbetapir) and CSF Aβ 1–42, t-tau, p-tau, global [18 F]FDG (SUVR). A total of 253 subjects (CN 54, EMCI 128, LMCI 40, AD 31) from ADNI dataset were analyzed. CSF Aβ 1–42, t-tau, p-tau and PET scan were obtained in the same individual not more than 6 months apart. Voxel-based SUVR maps for [11 C]PIB and [18 F]florbetapir were calculated using the cerebellar cortex as a reference region. Global SUV was estimated as the median SUVR value obtained using masks encompassing fronto-temporo-parietal regions. A cross-sectional linear and non-linear analysis was conducted between CSF and imaging biomarkers. Demographic data is presented in Table 1. The associations between CSF Aβ 1–42 and regional [18 F]florbetapir or [11 C]PIB binding were better described by an exponential decay model. The associations between Aβ 1–42 and [18 F]florbetapir or [11 C]PIB were similar in frontal, posterior parietal, temporal, precuneus and posterior cingulated areas (t>4.5; Figure 1). No associations between Aβ 1–42 and amyloid imaging agents were observed in the white matter and brain stem regions. Individuals with CSF Aβ 1–42 value over 200 pg/mL did not show [11 C]PIB uptake in cortical areas. In contrast, both amyloid-imaging agents showed linear association with t-tau and p-tau. CSF t-tau and p-tau showed significant correlation with [11 C]PIB uptake in a small cluster in the frontal area. In contrast, CSF t-tau or p-tau showed correlation with [18 F]florbetapir in frontal, temporal and parietal brain regions. No correlation was shown between global [18 F]FDG SUVR and the binding of amyloid imaging agents (Figure1). The pattern of regional deposition of fibrillary amyloid in the brain is non-linearly associated with CSF A b 1–42 concentrations. However the link between p-tau, t-tau and fibrillary amyloid deposition seems to be dependent on the amyloid-imaging agent. While imaging and CSF measures of amyloid pathology are equivalent, [18 F]FDG uptake seems to provide independent information from regional deposition of fibrillary amyloid. (A) showed the association between [C]PIB and CSF biomarkers, [F]FDG(SUVr). (B) showed the association between [F]florbetapir and CSF biomarkers, [F] FDG(SUVr).

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0080.002

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.018
GPT teacher head0.271
Teacher spread0.253 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueAlzheimer s & Dementia→Same topicDementia and Cognitive Impairment Research→French-language works237,207→