Role of Tyrosine Kinase Receptors in Angiotensin II AT2 Receptor Signaling: Involvement in Neurite Outgrowth and in p42/p44mapk Activation in NG108-15 Cells
Bibliographic record
Abstract
NG108-15 cells, which have a rounding-up morphology when cultured in serum-supplemented medium, extend neurites when stimulated for 3 d with angiotensin II (Ang II). The aim of the present study was to investigate whether growth factor receptors are necessary for mediating the effects of Ang II. A 3-d treatment with AG879, an inhibitor of nerve growth factor receptor TrkA, strongly affected neurite outgrowth and phosphorylation of p42/p44(mapk) induced by Ang II. PD168393, an inhibitor of epidermal growth factor (EGF) receptor slightly decreased Ang II-induced neurite outgrowth, whereas AG213, an inhibitor of both platelet-derived growth factor receptor and EGF receptor, stimulated neurite outgrowth and p42/p44(mapk) phosphorylation on its own, without affecting further stimulation with Ang II. Moreover, Ang II induced the phosphorylation of TrkA (maximum at 5 min of incubation in the presence of serum or at 20 min in cells depleted in serum for 2 h) and a rapid increase in Rap1 activity, both effects abolished in cells preincubated with 10 microm AG879. In summary, the present results demonstrate that AT(2) receptor-induced sustained activation of p42/p44(mapk) and corresponding neurite outgrowth are mediated by phosphorylation of the nerve growth factor TrkA receptor. However, the results also point out that the presence of other growth factors, such as EGF or PDFG, may interfere with the effect of Ang II. Altogether, the current findings clearly indicate that the effects of the AT(2) receptor on neurite outgrowth dynamics are modulated by the presence of growth factors in the culture medium.
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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".