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Record W2069251666 · doi:10.1016/j.jalz.2011.09.101

P4‐356: MRI‐derived cortical thickness measurements from APP transgenic mice

2011· article· en· W2069251666 on OpenAlexaff
François Hébert, Ming‐Kai Ho, Jason P. Lerch, Édith Hamel, Barry J. Bedell

Bibliographic record

VenueAlzheimer s & Dementia · 2011
Typearticle
Languageen
FieldMedicine
TopicAlzheimer's disease research and treatments
Canadian institutionsSickKids FoundationUniversity of TorontoMcGill UniversityHospital for Sick ChildrenMontreal Neurological Institute and Hospital
Fundersnot available
KeywordsMagnetic resonance imagingGenetically modified mouseCerebral cortexPathologyMedicineBiologyAnatomyNeuroscienceTransgeneRadiology

Abstract

fetched live from OpenAlex

Quantitative analysis of anatomical MRI data has proven to be an exceptionally valuable tool in Alzheimer's disease (AD) studies. Studies employing sophisticated methods for extraction of the cortical surface from MR images of the human brain have demonstrated that cortical thickness measurements allow for monitoring of disease progression. While a number of groups have reported volumetric changes in the brains of mouse models of AD, cortical thickness measurement from in vivo MRI data have not been assessed. In this study, we have utilized a fully-automated approach for the measurement of cortical thickness using anatomical MRI data acquired from mutant human amyloid precursor protein (APP) transgenic mice ranging from 3 to 19 months-of-age. Anatomical MRI data was acquired from 3-4 month-old (young group), 10-12 month-old (middle-aged group), 18-19 month-old (old group) APP TG (J20 line) and wild-type (WT) mice (n = 20 mice per group). Images were acquired from anesthetized mice using a 3D balanced steady-state free-precession (b-SSFP) pulse sequence and a 7T Bruker Pharmascan system. A field-of-view of 1.8 × 1.8 × 0.9 cm allowed for whole brain coverage and an isotropic spatial resolution of 140×140×140 micrometers provided good delineation of the mouse neuroanatomy. The cortical surface from each mouse brain was labeled using an automated, atlas-based approach and the cortical thickness was measured at each vertex across the entire cortical mantle. ROI-based analysis was performed on the cortical thickness maps. The cerebral cortex of APP TG mice was thicker than that of the WT mice in the young group. The entorhinal, frontal, and temporal-parietal cortices demonstrated an age-dependent thinning in the APP mice, while no change or increasing thickness was observed in WT mice. We have demonstrated regional differences in MRI-derived cortical thickness measures between APP TG and WT mice at different ages. Given that the young APP TG mice, which do not exhibit beta-amyloid plaques, demonstrated increased cortical thickness relative to age-matched WT mice implicates pathological processes other than beta-amyloid deposition as contributors to quantitative MRI measures. A greater understanding of these underlying factors should translate to improved interpretation of cortical thickness measures in human AD MRI studies.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.002

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 head0.096
GPT teacher head0.309
Teacher spread0.214 · 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 designBench or experimental
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

Citations0
Published2011
Admission routes1
Has abstractyes

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