p38MAPK Inhibition Enhances Basal and Norepinephrine-Stimulated p42/44MAPK Phosphorylation in Rat Pinealocytes**This work was supported by grants from the Medical Research Council of Canada.
Bibliographic record
Abstract
Interaction between p38MAPK and p42/44MAPK in rat pinealocytes was examined by determining the effects of p38MAPK inhibitors on the phosphorylation of p42/44MAPK using Western blot analysis. Treatment with SB202190, a specific inhibitor of p38MAPK, increased p42/44MAPK phosphorylation in a concentration-dependent manner. SB202190 also enhanced the magnitude and the duration of norepinephrine-activated p42/44MAPK phosphorylation. The effect of SB202190 on p42/44MAPK phosphorylation was abolished by PD98059 or UO126, inhibitors of MEK, suggesting that SB202190 is acting upstream of MEK in activating p42/44MAPK. The SB202190-induced phosphorylation of p42/44MAPK was not blocked by inhibitors of cGMP-dependent kinase (KT5823), protein kinase C (calphostin C) or Ca2+/calmodulin dependent kinase (KN93) suggesting that these pathways may not be involved in the effect of SB202190. SB202190 further increased p42/44MAPK phosphorylation that was stimulated by 8-bromo-cGMP, 4beta phorbol 12-myristate 13-acetate, or ionomycin. In contrast, inhibition of p42/44MAPK phosphorylation by dibutyryl-cAMP persisted when p42/44MAPK phosphorylation was increased by SB202190. Furthermore, inhibition of p42/44MAPK phosphorylation had no effect on p38MAPK activation. These results suggest that inhibition of p38MAPK causes activation of p42/44MAPK and acts synergistically with norepinephrine in the regulation of p42/44MAPK activation in rat pinealocytes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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) | 0.002 | 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".