Isoform Specificity of PKC Translocation in Living<i>Aplysia</i>Sensory Neurons and a Role for Ca<sup>2+</sup>-Dependent PKC APL I in the Induction of Intermediate-Term Facilitation
Bibliographic record
Abstract
Protein kinase Cs (PKCs) are important effectors of synaptic plasticity. In Aplysia, there are two major phorbol ester-activated PKCs, Ca2+-activated PKC Apl I and Ca2+-independent PKC Apl II. Functional Apl II, but not Apl I, in sensory neurons is required for a form of short-term facilitation induced at sensorimotor synapses by the facilitatory transmitter serotonin (5-HT). Because PKCs are activated by translocating from the cytoplasm to the membrane, we used fluorescently tagged PKCs to determine the isoform and cell-type specificity of translocation in living Aplysia neurons. In Sf9 cells, low levels of diacylglycerol translocate Apl II, but not Apl I, which requires calcium for translocation at low concentrations of diacylglycerol. Accordingly, application of 5-HT to Aplysia sensory neurons in the absence of neuronal firing translocates Apl II, but not Apl I, consistent with the role of Apl II in short-term facilitation. This translocation is observed in sensory neurons, but not in motor neurons. Apl I translocates only if 5-HT is coupled to firing in the sensory neuron; firing alone is ineffective. Because combined 5-HT and firing are required for the induction of one type of intermediate-term facilitation at these synapses, we asked whether this form of synaptic plasticity involves activation of Apl I. We report here that dominant-negative Apl I, but not Apl II, blocks intermediate-term facilitation. Thus, different isoforms of PKC translocate under different conditions to mediate distinct types of synaptic plasticity: Ca2+-independent Apl II is involved in short-term facilitation, and Ca2+-dependent Apl I contributes to 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".