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Record W2225105236 · doi:10.1016/j.jalz.2015.06.047

IC‐P‐027: Dynamics of longitudinal biomarker changes in the Mcgill‐R‐Thy1‐APP RAT

2015· article· en· W2225105236 on OpenAlexaffabout
Monica Shin, Maxime Parent, Vladimir Fonov, Min-Su Kang, Axel Mathieu, S.T.M. Allard, Sonia Do Carmo, Serge Gauthier, A. Claudio Cuello, Pedro Rosa‐Neto

Bibliographic record

VenueAlzheimer s & Dementia · 2015
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBioinformatics and Genomic Networks
Canadian institutionsMcGill Genome CentreDouglas Mental Health University InstituteDouglas CollegeMcGill UniversityMcGill University Health CentreTranslational Research in Oncology
Fundersnot available
KeywordsVoxelSomatosensory systemNeuroscienceTemporal lobeBiomarkerGenetically modified mouseNeuroimagingPathologyNuclear medicineInternal medicinePsychologyChemistryMedicineTransgeneBiochemistryRadiology

Abstract

fetched live from OpenAlex

Rat transgenic models of human brain amyloidosis constitute a unique opportunity to explore the impact of amyloid pathology on imaging biomarkers without the bias of tau pathology invariably present in the human brain. Due to its size, the McGill-R-Thy1-APP rat is ideal for multi-modal neuroimaging observations as compared to transgenic mouse. Here, we studied the associations between the rates of structural brain remodeling as a function of the rate of progression of hypometabolism in transgenic rats. We hypothesize regional specific interactions between biomarkers. McGill-R-Thy1-APP rat (n=9) and wild type (wt; n=12) had [18F]FDG and structural MRIs scans at 11-month (baseline) and 16-month (follow-up). Structural images were acquired using a Bruker 70/30USR Biospect MRI (FISP; TE/TR: 2.5/5.0ms; FOV: 3.6cm3; isotropic 250um voxels; 8 angles). Voxel-based morphometry was performed to obtain longitudinal deformation maps. [18F]FDG PET images were acquired and analyzed as described previously (3). For both scans, longitudinal difference maps were generated. Global uptake values obtained from these maps were then correlated with structural deformation maps using a voxel-level linear model. The olfactory bulb, anterior pituitary lobe, multiple cortical areas, lateral ventricle, and a portion of the hippocampus showed association between [18F]FDG declines and structural shrinkage. The left motor cortex and thalamic nuclei as well as the right primary somatosensory cortex showed dissociation between structural changes (expansion) and [18F]FDG declines. McGill-R-Thy1-APP allows for longitudinal biomarker measures without confounding effects of neurofibrillary tangles or cell death. In fact, the present results suggest that brain abnormal amyloid aggregates present in the McGill-R-Thy1-APP rat leads to expansion or shrinkage of grey matter structures and progressive hypometabolism. However these processes occur in synchrony in specific brain regions. These suggest a complex interface between amyloid pathology and pathophysiological mechanisms involved in structural declines in transgenic animals. t-stat map of regions that shrink when the metabolism decreases throughout the brain. t-stat map of regions that expand when the metabolism decreases throughout the brain.

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)0.000
metaresearch head score (Gemma)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.031
GPT teacher head0.262
Teacher spread0.231 · 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

Citations0
Published2015
Admission routes2
Has abstractyes

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