Modulation of nerve growth factor‐induced activation of MAP kinase in PC12 cells by inhibitors of nitric oxide synthase
Bibliographic record
Abstract
Nerve growth factor (NGF) increases expression of nitric oxide synthase (NOS) isozymes leading to enhanced production of nitric oxide (NO). NOS inhibitors attenuate NGF-mediated increases in cholinergic gene expression and neurite outgrowth. Mechanisms underlying this are unknown, but the mitogen-activated protein (MAP) kinase pathway plays an important role in NGF signaling. Like NGF, NO donors activate Ras leading to phosphorylation of MAP kinase. The present study investigated the role of NO in NGF-mediated activation of MAP kinase in PC12 cells. Cells were treated with 50 ng/mL NGF to establish the temporal pattern for rapid and sustained activation phases of MAP kinase kinase (MEK)-1/2 and p42/p44-MAP kinase. Subsequently, cells were pretreated with NOS inhibitors Nomega-nitro-L-arginine methylester and s-methylisothiourea and exposed to NGF for up to 24 h. NGF-induced activation of MEK-1/2 and p42/p44-MAP kinase was not dependent on NO, but sustained phosphorylation of MAP kinase was modulated by NO. This modulation did not occur at the level of Ras-Raf-MEK signaling or require activation of cGMP/PKG pathway. NOS inhibitors did not affect NGF-mediated phosphorylation of MEK. Expression of constitutively active-MEKK1 in cells led to phosphorylation of p42/p44-MAP kinase and robust neurite outgrowth; constitutively active-MKK1 also caused differentiation with neurite extension. NOS inhibitor treatment of cells expressing constitutively active kinases did not affect MAP kinase activation, but neurite outgrowth was attenuated. NOS inhibitors did not alter NGF-mediated nuclear translocation of phospho-MAP kinase, but phosphorylated kinases disappeared more rapidly from NOS inhibitor-treated cells suggesting greater phosphatase activity and termination of sustained activation of MAP kinase.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.001 | 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".