Early Growth Response 1 (Egr-1) Regulates N-Methyl-d-aspartate Receptor (NMDAR)-dependent Transcription of PSD-95 and α-Amino-3-hydroxy-5-methyl-4-isoxazole Propionic Acid Receptor (AMPAR) Trafficking in Hippocampal Primary Neurons
Bibliographic record
Abstract
The N-methyl-d-aspartate receptor (NMDAR) controls synaptic plasticity and memory function and is one of the major inducers of transcription factor Egr-1 in the hippocampus. However, how Egr-1 mediates the NMDAR signal in neurons has remained unclear. Here, we show that the hippocampus of mice lacking Egr-1 displays electrophysiology properties and ultrastructure that are similar to mice overexpressing PSD-95, a major scaffolding protein of postsynaptic density involved in synapse formation, synaptic plasticity, and synaptic targeting of AMPA receptors (AMPARs), which mediate the vast majority of excitatory transmission in the CNS. We demonstrate that Egr-1 is a transcription repressor of the PSD-95 gene and is recruited to the PSD-95 promoter in response to NMDAR activation. Knockdown of Egr-1 in rat hippocampal primary neurons blocks NMDAR-induced PSD-95 down-regulation and AMPAR endocytosis. Likewise, overexpression of Egr-1 in rat hippocampal primary neurons causes reduction in PSD-95 protein level and promotes AMPAR endocytosis. Our data indicate that Egr-1 is involved in NMDAR-mediated PSD-95 down-regulation and AMPAR endocytosis, a process important in the expression of long term depression.
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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 | 0.000 | 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) | 0.001 | 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".