Age-related attenuation of cortical synaptic tagging in the ACC is rescued by BDNF or a TrkB receptor agonist in both sex of mice
Bibliographic record
Abstract
Long-term potentiation (LTP) is a key cellular mechanism for learning and memory, and recent studies in the hippocampus found that LTP was impaired in aged animals. Previous studies of cortical LTP have focused primarily on the homosynaptic plasticity in adult mice, while fewer studies have looked at heterosynaptic plasticity-such as synaptic tagging in aged mice. In the present study, we investigated synaptic tagging in adult and middle-aged mice's anterior cingulate cortex (ACC) using the 64-channel multielectrode dish (MED64) recording system. We found that synaptic tagging was impaired in the ACC of middle-aged male mice as compared to adult mice. Both the network late-phase LTP (L-LTP) and the recruitment of inactive responses were reduced in the ACC of middle-aged male mice. Similar results were found in female middle-aged mice, indicating that there is no gender difference. Furthermore, bath application of brain-derived neurotrophic factor (BDNF) or systemic treatment with newly developed TrkB receptor agonists R13, was shown to rescue both synaptic tagging, and L-LTP, in middle-aged mice. To determine the distribution of synaptic LTP within the ACC, a new visualization method was developed to map the Spatio-temporal variation of LTP in the ACC. Our results provide strong evidence that cortical potentiation and synaptic tagging show an age-dependent reduction, and point to the TrkB receptor as a potential drug target for the treatment of memory decline.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".