Early Growth Response 2 (Egr2) Induction by Neuronal Activity-dependent Nuclear Factor Kappa B (NF-κB) Activation
Bibliographic record
Abstract
Nuclear factor kappa B (NF-κB) mediated signalling is complex and plays a critical role in many biological processes. Investigators have reported that NF-κB is activated during the induction of long term potentiation (LTP), a proposed mechanism for memory encoding, and may be a requirement for synaptic plasticity and memory. In this study, mRNA extracted from hippocampal slices of NF-kB p50 knockout mice and its littermate before and after induction of LTP was analyzed using DNA microarray analysis (Affy-metrix GeneChip® Mouse Genome 430 2.0) to explore candidate target genes of NF-kB in LTP. The early growth response 2 (Egr-2) was identified as one putative NF-kB target gene. Egr-2 mRNA and protein analysis of primary cortical neurons and HeLa cells chemically stimulated with Tumor Necrosis Factor α (TNFα) to activate the NF-kB sig-nalling pathway confirmed the microarray results. In addition, examination of the Egr-2 promoter sequence for NF-kB binding sites using chromatin immunoprecipitation (ChIP) and electrophoretic mobility shift assays (EMSA) confirmed promoter occupancy and specificity of binding in vivo, respectively. These data suggest that Egr-2 expression level is controlled by direct transcriptional activity of the NF-kB transcription factor.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".