[P1–201]: REST HIPPOCAMPAL AND CORTICAL LEVELS CORRELATE WITH COGNITIVE PERFORMANCE IN A RAT MODEL OF EARLY ALZHEIMER'S DISEASE
Bibliographic record
Abstract
The gene silencing transcription factor (REST)/neuron-restrictive silencer factor (NRFS) is a candidate to control neuronal function from fetal development to aging. REST is downregulated after neuronal differentiation and during adulthood, it is found in human and murine brains at basal levels. REST begins to increase in aging, conferring resistance and protection against oxidative stress and toxic insults associated with Alzheimer disease (AD). However, REST hippocampal and cortical levels are not increased in AD patients. REST levels were measured by western blots from prefrontal cortex and hippocampus samples at different rat ages (3, 6, 12 and 18 months old) of wild type (controls) and an early-Alzheimer transgenic rat model. Hemizygous McGill-R-Thy1-APP overproduces and accumulates human beta-amyloid protein (Leon, 2010) and display cognitive deficits started at 13 to 15 months old, tested in Morris water maze and probe tests. We found a significantly increased REST levels starting as soon as six months old in cortex of transgenic rats with a positive correlation through age (Pearson, r = 0,9962) from 3 to 12 months old, compared to age-matched control rats. However, REST levels were significantly decreased at 18 months old in transgenic rats, compared to control rats. REST downregulation at 18 months old correlates with deficits in cognitive performance of transgenic rats compared to age-matched controls tested by Morris water maze and Probe test. At aging, REST begins to increase to confer protection again toxic and oxidative stress insults. In our early-Alzheimer transgenic rat model, REST levels begin to increase early during adulthood, suggesting a protective mechanism which could allow transgenic rats to preserve intact cognitive functions, as compared to age-matched controls. However, hemizygous McGill-R-Thy1-APP rats overproduces and accumulates human beta-amyloid protein at 18 months old which negatively correlates with REST levels. This data should render suitable preclinical proof of principle for further REST clinical manipulation.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".