Altered neurochemical profile in the <scp>M</scp>cGill‐<scp>R</scp>‐<scp>T</scp>hy1‐<scp>APP</scp> rat model of <scp>A</scp>lzheimer's disease: a longitudinal <i>in vivo</i><sup>1</sup>H <scp>MRS</scp> study
Bibliographic record
Abstract
We investigated metabolite levels during the progression of pathology in McGill-R-Thy1-APP rats, a transgenic animal model of Alzheimer's disease, and in healthy age-matched controls. Rats were subjected to in vivo (1) H magnetic resonance spectroscopy (MRS) of the dorsal hippocampus at age 3, 9 and 12 months and of frontal cortex at 9 and 12 months. At 3 months, a stage in which only Aβ oligomers are present, lower glutamate, myo-inositol and total choline content were apparent in McGill-R-Thy1-APP rats. At age 9 months, lower levels of glutamate, GABA, N-acetylaspartate and total choline and elevated myo-inositol and taurine were found in dorsal hippocampus, whereas lower levels of glutamate, GABA, glutamine and N-acetylaspartate were found in frontal cortex. At age 12 months, only the taurine level was significantly different in dorsal hippocampus, whereas taurine, myo-inositol, N-acetylaspartate and total creatine levels were significantly higher in frontal cortex. McGill-R-Thy1-APP rats did not show the same changes in metabolite levels with age as displayed in the controls, and overall, prominent and complex metabolite differences were evident in this transgenic rat model of Alzheimer's disease. The findings also demonstrate that in vivo (1) H MRS is a powerful tool to investigate disease-related metabolite changes in 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".