Neurochemical and cognitive changes precede structural abnormalities in the TgF344-AD rat model
Bibliographic record
Abstract
Abstract Alzheimer’s disease is a progressive neurodegenerative disorder with a decades-long pre-symptomatic phase, substantiating the need for prodromal biomarker development and early intervention. To deconstruct the processes underlying disease progression and identify potential biomarkers, we used neuroimaging techniques with high translational potential to human clinical studies in the TgF344-AD rat model which recapitulates the full spectrum of Alzheimer’s neuropathology (progressive amyloid deposition, tauopathy, frank neuronal loss, gliosis, and cognitive dysfunction). We employed longitudinal MRI and magnetic resonance spectroscopy in conjunction with behavioural testing to characterize multiple facets of disease pathology in male and female TgF344-AD rats (n = 26, 14M/12F) relative to wildtype littermates (n = 24, 12M/12F). Testing was performed at 4, 10, 16, and 18 months, covering much of the adult rat lifespan and multiple stages of disease progression. The TgF344-AD model demonstrated impaired spatial reference memory in the Barnes Maze by 4 months of age, followed by neurochemical abnormalities in the hippocampus by 10 months and major structural changes by 16 months. Specifically, TgF344-AD rats displayed increased total choline and lactate, and decreased total creatine, taurine, and N-acetylaspartate to myo-inositol ratio, dentate gyrus hypertrophy, and atrophy in the hippocampus, hypothalamus, and nucleus accumbens. Overall, these findings support the use of MRI and magnetic resonance spectroscopy for the development of non-invasive biomarkers of disease progression, clarify the timing of pathological feature presentation in this model, and contribute to the validation of the TgF344-AD rat as a highly relevant model for pre-clinical Alzheimer’s disease research.
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 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) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 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) | 0.002 | 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".