Chromaffin Cell F-actin Disassembly and Potentiation of Catecholamine Release in Response to Protein Kinase C Activation by Phorbol Esters Is Mediated through Myristoylated Alanine-rich C Kinase Substrate Phosphorylation
Bibliographic record
Abstract
The large majority of chromaffin vesicles are excluded from the plasma membrane by a cortical F-actin network. Treatment of chromaffin cells with phorbol 12-myristate 13-acetate produces disassembly of cortical F-actin, increasing the number of vesicles at release sites (Vitale, M. L., Seward, E. P., and Trifaró, J. M. (1995) Neuron 14, 353-363). Here, we provide evidence for involvement of myristoylated alanine-rich protein kinase C substrate (MARCKS), a protein kinase C substrate, in chromaffin cell secretion. MARCKS binds and cross-links F-actin, the latter is inhibited by protein kinase C-induced MARCKS phosphorylation. MARCKS was found in chromaffin cells by immunoblotting. MARCKS was also detected by immunoprecipitation. In intact or permeabilized cells MARCKS phosphorylation increased upon stimulation with 10(-7) m phorbol 12-myristate 13-acetate. This was accompanied by cortical F-actin disassembly and potentiation of secretion. MARCKS phosphorylation, cortical F-actin disassembly, and potentiation of Ca(2+)-evoked secretion were inhibited by a peptide (MARCKS phosphorylation site domain sequence (MPSD)) with amino acid sequence corresponding to MARCKS phosphorylation site. MPSD was phosphorylated in the process. A similar peptide (alanine-substituted phosphorylated site domain) with four serine residues of MPSD substituted by alanines was ineffective. These results provide the first evidence for MARCKS involvement in chromaffin cell secretion and suggest that regulation of cortical F-actin cross-linking might be involved in this process.
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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".