IC‐P‐027: Dynamics of longitudinal biomarker changes in the Mcgill‐R‐Thy1‐APP RAT
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".