Inhibition of p38 Mitogen-Activated Protein Kinase Enhances Adrenergic-Stimulated Arylalkylamine N-Acetyltransferase Activity in Rat Pinealocytes
Bibliographic record
Abstract
We have previously shown that inhibition of p38(MAPK) increases adrenergic-stimulated p42/44(MAPK) activation in rat pinealocytes. In this study we investigated whether p38(MAPK) played a role in the adrenergic regulation of arylalkylamine-N-acetyltransferase (AA-NAT) induction and melatonin (MT) synthesis. Treatment of pinealocytes with norepinephrine (NE) caused a time-dependent increase in the levels of AA-NAT mRNA, AA-NAT protein, and enzymatic activity as well as MT production. Cotreatment with SB202190, a selective p38(MAPK) inhibitor, although having no effect on AA-NAT activity or protein level 3 h after NE treatment, caused a sustained increase in AA-NAT activity and protein level after 6 h of NE treatment. The increases in NE-stimulated AA-NAT activity and protein level by SB202190 occurred in the absence of an increase in AA-NAT mRNA. Similar results were obtained when AA-NAT was induced by (Bu)(2)cAMP or when SB203580 was used to inhibit p38(MAPK). In comparison, SB202474, the inactive analog, had no effect on NE or (Bu)(2)cAMP-stimulated AA-NAT activity or protein level. SB202190 also increased cumulative NE-stimulated MT production, provided that the medium was supplemented with 5-methoxytryptamine. p38(MAPK) inhibitors had no effect on hydroxyindole-O-methyltransferase activity. These results show that inhibition of p38(MAPK), although having no effect on cAMP-mediated AA-NAT transcription, appears to increase AA-NAT activity either by increasing translation or by reducing degradation of the AA-NAT protein. The lack of effect on NE-stimulated MT accumulation by p38(MAPK) inhibitors in the absence of 5-methoxytryptamine could be secondary to a lack of substrate, or alternatively, hydroxyindole-O-methyltransferase may become limiting.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".