Activation of Rac1-dependent redox signaling is critically involved in staurosporine-induced neurite outgrowth in PC12 cells
Bibliographic record
Abstract
Staurosporine, a non-specific protein kinase inhibitor, has been shown to induce neurite outgrowth in PC12 cells, but the mechanism by which staurosporine induces neurite outgrowth is still obscure. In the present study, we investigated whether the activation of Rac1 was responsible for the neurite outgrowth triggered by staurosporine. Staurosporine caused rapid neurite outgrowth independent of the ERK signaling pathways. In contrast, neurite outgrowth in response to staurosporine was accompanied by activation of Rac1, and the Rac1 inhibitor NSC23766 attenuated the staurosporine-induced neurite outgrowth in a concentration-dependent manner. In addition, suppression of Rac1 activity by expression of the dominant negative mutant Rac1N17 also blocked the staurosporine-induced morphological differentiation of PC12 cells. Staurosporine caused an activation of NADPH oxidase and increased the production of reactive oxygen species (ROS), which was prevented by NSC23766 and diphenyleneiodonium (DPI), an NADPH oxidase inhibitor. Staurosporine-induced neurite outgrowth was attenuated by pretreatment with DPI and exogenous addition of sublethal concentration of H2O2 accelerated neurite outgrowth triggered by staurosporine. These results indicate that activation of Rac1, which leads to ROS generation, is required for neurite outgrowth induced by staurosporine in PC12 cells.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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 | 0.000 |
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".