Molecular mechanisms associated with peptidergic control of adrenergic function
Bibliographic record
Abstract
Phenylethanolamine N‐methyltransferase (PNMT), which produces epinephrine, is a marker of adrenergic function. While pituitary adenylate cyclase activating polypeptide (PACAP), independently and cooperatively with NGF, activates PNMT promoter‐driven and endogenous PNMT gene expression in PC12 cells, molecular mechanisms remain unknown. Transfection assays in PC12 cells and PKA‐deficient and PLCγ1‐deficient PC12 cells using PNMT promoter‐luciferase gene constructs and signaling inhibitors showed that PLCγl and cAMP‐dependent PKA signaling are critical for PACAP activation and PI3K, PKC, ERK1/2 MAPK, p38 MAPK downstream. The inhibitors also abrogated PACAPergic induction of endogenous PNMT. Western analysis of nuclear protein from PACAP‐treated PC12 cells showed that Egr‐1 and AP‐2 underlie PACAP responses. Results with nested deletion or site‐directed mutant constructs support this possibility. Exposure of PACAP‐treated transfected and untransfected PC12 cells to histone deacetylase (HDAC) inhibitors, Na butyrate or Trichostatine A, incrementally activated the PNMT promoter and endogenous PNMT. Findings indicate that PACAP transcriptionally activates the PNMT gene with HDAC being limiting. Presence of long and short forms of PNMT mRNA further suggest post‐transcriptional regulation by PACAP. Support: Spunk Fund, Inc., Sobel‐Keller Fund and McLean Hospital.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".