p300/CBP-Associated Factor Selectively Regulates the Extinction of Conditioned Fear
Bibliographic record
Abstract
It is well established that the activity of chromatin-modifying enzymes is crucial for regulating gene expression associated with hippocampal-dependent memories. However, very little is known about how these epigenetic mechanisms influence the formation of cortically dependent memory, particularly when there is competition between opposing memory traces, such as that which occurs during the acquisition and extinction of conditioned fear. Here we demonstrate, in C57BL/6 mice, that the activity of p300/CBP-associated factor (PCAF) within the infralimbic prefrontal cortex is required for long-term potentiation and is necessary for the formation of memory associated with fear extinction, but not for fear acquisition. Further, systemic administration of the PCAF activator SPV106 enhances memory for fear extinction and prevents fear renewal. The selective influence of PCAF on fear extinction is mediated, in part, by a transient recruitment of the repressive transcription factor ATF4 to the promoter of the immediate early gene zif268, which competitively inhibits its expression. Thus, within the context of fear extinction, PCAF functions as a transcriptional coactivator, which may facilitate the formation of memory for fear extinction by interfering with reconsolidation of the original memory trace.
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) | 0.000 | 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) | 0.001 | 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 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".