Reactive Oxygen Species Are Required for 5-HT-Induced Transactivation of Neuronal Platelet-Derived Growth Factor and TrkB Receptors, but Not for ERK1/2 Activation
Bibliographic record
Abstract
High concentrations of reactive oxygen species (ROS) induce cellular damage, however at lower concentrations ROS act as intracellular second messengers. In this study, we demonstrate that serotonin (5-HT) transactivates the platelet-derived growth factor (PDGF) type β receptor as well as the TrkB receptor in neuronal cultures and SH-SY5Y cells, and that the transactivation of both receptors is ROS-dependent. Exogenous application of H₂O₂ induced the phosphorylation of these receptors in a dose-dependent fashion, similar to that observed with 5-HT. However the same concentrations of H₂O₂ failed to increase ERK1/2 phosphorylation. Yet, the NADPH oxidase inhibitors diphenyleneiodonium chloride and apocynin blocked both 5-HT-induced PDGFβ receptor phosphorylation and ERK1/2 phosphorylation. The increases in PDGFβ receptor and ERK1/2 phosphorylation were also dependent on protein kinase C activity, likely acting upstream of NADPH oxidase. Additionally, although the ROS scavenger N-acetyl-l-cysteine abrogated 5-HT-induced PDGFβ and TrkB receptor transactivation, it was unable to prevent 5-HT-induced ERK1/2 phosphorylation. Thus, the divergence point for 5-HT-induced receptor tyrosine kinase (RTK) transactivation and ERK1/2 phosphorylation occurs at the level of NADPH oxidase in this system. The ability of 5-HT to induce the production of ROS resulting in transactivation of both PDGFβ and TrkB receptors may suggest that instead of a single GPCR to single RTK pathway, a less selective, more global RTK response to GPCR activation is occurring.
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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 | 0.000 |
| 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".