The Lysine Acetyltransferase PCAF Functionally Interacts with Estrogen Receptor Alpha in the Hippocampus of Gonadally Intact Male—But Not Female—Rats to Enhance Short-Term Memory
Bibliographic record
Abstract
Acetylation of histone proteins by histone acetyltransferases (HATs), and the resultant change in gene expression, is a well-established mechanism necessary for long-term memory (LTM) consolidation, which is not required for short-term memory (STM). However, we previously demonstrated that the HAT p300/CBP-associated factor (PCAF) also influences hippocampus (HPC)-dependent STM in male rats. In addition to their epigenetic activity, HATs acetylate nonhistone proteins involved in nongenomic cellular processes, such as estrogen receptors (ERs). Given that ERs have rapid, nongenomic effects on HPC-dependent STM, we investigated the potential interaction between ERs and PCAF for STM mediated by the dorsal hippocampus (dHPC). Using a series of pharmacological agents administered directly into the dHPC, we reveal a functional interaction between PCAF and ERα in the facilitation of short-term object-in-place memory in male but not female rats. This interaction was specific to ERα, while ERβ agonism did not enhance STM. It was further specific to dHPC STM, as the effect was not present in the dHPC for LTM or in the perirhinal cortex. Further, while STM required local (i.e., dHPC) estrogen synthesis, the facilitatory interaction effect appeared independent of estrogens. Finally, western blot analyses demonstrated that PCAF activation in the dHPC rapidly (5 min) activated downstream estrogen-related cell signaling kinases (c-Jun N-terminal kinase and extracellular signal-related kinase). Collectively, these findings indicate that PCAF, which is typically implicated in LTM through epigenetic processes, also influences STM in the dHPC, possibly via nongenomic ER activity. Critically, this novel PCAF-ER interaction might exist as a male-specific mechanism supporting STM.
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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 | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".