Role of Protein Kinase C in the Induction and Maintenance of Serotonin-Dependent Enhancement of the Glutamate Response in Isolated Siphon Motor Neurons of<i>Aplysia californica</i>
Bibliographic record
Abstract
Serotonin (5-HT) mediates learning-related facilitation of sensorimotor synapses in Aplysia californica. Under some circumstances 5-HT-dependent facilitation requires the activity of protein kinase C (PKC). One critical site of PKC's contribution to 5-HT-dependent synaptic facilitation is the presynaptic sensory neuron. Here, we provide evidence that postsynaptic PKC also contributes to synaptic facilitation. We investigated the contribution of PKC to enhancement of the glutamate-evoked potential (Glu-EP) in isolated siphon motor neurons in cell culture. A 10 min application of either 5-HT or phorbol ester, which activates PKC, produced persistent (> 50 min) enhancement of the Glu-EP. Chelerythrine and bisindolylmaleimide-1 (Bis), two inhibitors of PKC, both blocked the induction of 5-HT-dependent enhancement. An inhibitor of calpain, a calcium-dependent protease, also blocked 5-HT's effect. Interestingly, whereas chelerythrine blocked maintenance of the enhancement, Bis did not. Because Bis has greater selectivity for conventional and novel isoforms of PKC than for atypical isoforms, this result implicates an atypical isoform in the maintenance of 5-HT's effect. Although induction of enhancement of the Glu-EP requires protein synthesis (Villareal et al., 2007), we found that maintenance of the enhancement does not. Maintenance of 5-HT-dependent enhancement appears to be mediated by a PKM-type fragment generated by calpain-dependent proteolysis of atypical PKC. Together, our results suggest that 5-HT treatment triggers two phases of PKC activity within the motor neuron, an early phase that may involve conventional, novel or atypical isoforms of PKC, and a later phase that selectively involves an atypical isoform.
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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) | 0.001 | 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".