Suppression of a MEF2-KLF6 Survival Pathway by PKA Signaling Promotes Apoptosis in Embryonic Hippocampal Neurons
Bibliographic record
Abstract
In the mammalian nervous system, regulation of transcription factor activity is a crucial determinant of neuronal cell survival, differentiation, and death. The myocyte enhancer factor 2 (MEF2) transcription factors have been implicated in cellular processes underlying neuronal survival and differentiation. A core component of the MEF2 complex is the MEF2D subunit. Recently, we reported that cAMP-dependent protein kinase (cAMP/PKA) signaling negatively regulates MEF2D function in myogenic cells. Here, we assessed whether cAMP signaling converges on the prosurvival role of MEF2D in Sprague Dawley rat embryonic (E18) hippocampal neurons. Initially, we observed that experimental induction of cAMP/PKA signaling promotes apoptosis in primary hippocampal neurons as indicated by TUNEL and FACS analysis. Luciferase reporter gene assays revealed that PKA potently represses MEF2D trans-activation properties in neurons. This effect was largely reversed by engineered neutralizing mutations of PKA phospho-acceptor sites on MEF2D (S121/190A). Krüppel-like factor 6 (KLF6) was identified as a key transcriptional target of MEF2 in hippocampal neurons, and siRNA-mediated knockdown of KLF6 expression promotes neuronal cell death and also antagonizes the prosurvival role of MEF2D. These observations have important implications for understanding the pathways controlling cell survival and death in the mammalian nervous system.
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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) | 0.000 | 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 | 0.000 |
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".