Regulation of catecholamine biosynthetic enzymes by nitric oxide
Bibliographic record
Abstract
The neurotransmitters/neurohormones catecholamines (CA) are involved in the sympathetic control of arterial blood pressure and cardiac function. Recent studies show that nitric oxide (NO) can regulate the release of CA from the adrenal medulla. The in vitro PC12 cell line was used to examine the effect of NO on the regulation of the CA biosynthetic enzymes: tyrosine hydroxylase (TH), dopamine‐β‐hydroxylase (DBH) and phenylethanolamine N‐methyltransferase (PNMT). Results obtained from drug treatments with the NO donor, sodium nitroprusside (SNP) constitute an assessment of its effects in PC12 cells. Treatment of cells with SNP for 6 hours significantly increased TH and PNMT mRNA levels. Combination drug studies with SNP and intracellular kinase activators (forskolin, PMA, 8‐Br‐cGMP) and inhibitors for PKA (H‐89), cGMP (6‐anilinoquinone) PKG (DT‐2) and PKC (GF109203X) were also conducted. Increases in transcript levels for TH and PNMT were obtained under combination drug treatments of SNP and activators of PKA and PKG (p<0.05). mRNA transcript levels of TH, DBH and PNMT showed significant decreases when cells were pre‐treated with PKA, PKC and PKG inhibitors. Furthermore, preliminary transfections showed activation of the PNMT promoter by SNP treatment. Results from this study suggest that NO is capable of regulating CA biosynthetic enzymes, TH and PNMT via activation of the PKA and PKG pathways.
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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) | 0.001 | 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".