Serotonin-Induced Cleavage of the Atypical Protein Kinase C Apl III in<i>Aplysia</i>
Bibliographic record
Abstract
A constitutively active kinase, known as protein kinase Mζ (PKMζ), is proposed to act as a long-lasting molecular memory trace. While PKMζ is formed in rodents through translation of a transcript initiating in an intron of the protein kinase Cζ (PKCζ) gene, this transcript does not exist in Aplysia californica despite the fact that inhibitors of PKMζ erase memory in Aplysia in a fashion similar to rodents. We have previously shown that, in Aplysia, the ortholog of PKCζ, PKC Apl III, is cleaved by calpain to form a PKM after overexpression of PKC Apl III. We now show that kinase activity is required for this cleavage. We further use a FRET reporter to measure cleavage of PKC Apl III into PKM Apl III in live neurons using a stimulus that induces plasticity. Our results show that a 10 min application of serotonin induces cleavage of PKC Apl III in motor neuron processes in a calpain- and protein synthesis-dependent manner, but does not induce cleavage of PKC Apl III in sensory neuron processes. Furthermore, a dominant-negative PKM Apl III expressed in the motor neuron blocked the late phase of intermediate-term facilitation in sensory-motor neuron cocultures induced by 10 min of serotonin. In summary, we provide evidence that PKC Apl III is cleaved into PKM Apl III during memory formation, that the requirements for cleavage are the same as the requirements for the plasticity, and that PKM in the motor neuron is required for intermediate-term facilitation.
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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".