Glutamate presynaptic vesicular transporter and postsynaptic receptor levels correlate with spatial memory status in aging rat models
Bibliographic record
Abstract
In humans, memory capacities are generally affected with aging, even without any reported neurologic disorders. The mechanisms behind cognitive decline are not well understood. We studied here whether postsynaptic glutamate receptor and presynaptic vesicular glutamate transporters (VGLUTs) levels may change in the course of aging and be related to cognitive abilities using various age-impaired (AI) or age-unimpaired rat strains. Twenty-four-month-old Long-Evans (LE) rats with intact spatial memory maintained postsynaptic ionotropic glutamate receptor levels in the hippocampal-adjacent cortex similar to those of young animals. In contrast, AI rats showed significantly reduced expression of ionotropic glutamate receptor GluR2, NR2A and NR2B subunits. In AI LE rats, VGLUT1 and VGLUT2 levels were increased and negatively correlated with receptor levels as shown by principal component analysis and correlation matrices. We also investigated whether glutamatergic receptors and VGLUT levels were altered in the obesity-resistant LOU/C/Jall (LOU) rat strain which is characterized by intact memory despite aging. No difference was observed between 24-month-old LOU rats and their young counterparts. Taken together, the unaltered spatial memory performance of 24-month-old age-unimpaired LE and LOU rats suggests that intact coordination of the presynaptic and postsynaptic hippocampal-adjacent cortex glutamatergic networks may be important for successful cognitive aging. Accordingly, altered expression of presynaptic and postsynaptic glutamatergic components, such as in AI LE rats, could be considered a marker of age-related cognitive deficits.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".