Thrombin Enhances NGF-Mediated Neurite Extension via Increased and Sustained Activation of p44/42 MAPK and p38 MAPK
Bibliographic record
Abstract
Rapid neurite remodeling is fundamental to nervous system development and plasticity. It involves neurite extension that is regulated by NGF through PI3K/AKT, p44/42 MAPK and p38 MAPK. It also involves neurite retraction that is regulated by the serine protease, thrombin. However, the intracellular signaling pathway by which thrombin causes neurite retraction is unknown. Using the PC12 neuronal cell model, we demonstrate that thrombin utilizes the PI3K/AKT pathway for neurite retraction in NGF-differentiated cells. Interestingly, however, we found that thrombin enhances NGF-induced neurite extension in differentiating cells. This is achieved through increased and sustained activation of p44/42 MAPK and p38 MAPK. Thus, thrombin elicits opposing effects in differentiated and differentiating cells through activation of distinct signaling pathways: neurite retraction in differentiated cells via PI3K/AKT, and neurite extension in differentiating cells via p44/42 MAPK and p38 MAPK. These findings, which also point to a novel cooperative role between thrombin and NGF, have significant implications in the development of the nervous system and the disease processes that afflicts it as well as in the potential of combined thrombin and NGF therapy for impaired learning and memory, and spinal cord injury which all require neurite extension and remodeling.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".