Inhibitory responses in<i>Aplysia</i>pleural sensory neurons act to block excitability, transmitter release, and PKC Apl II activation
Bibliographic record
Abstract
Expression of the 5-HT(1Apl(a)) receptor in Aplysia pleural sensory neurons inhibited 5-HT-mediated translocation of the novel PKC Apl II in sensory neurons and prevented PKC-dependent synaptic facilitation at sensory to motoneuron synapses (Nagakura et al. 2010). We now demonstrate that the ability of inhibitory receptors to block PKC activation is a general feature of inhibitory receptors and is found after expression of the 5-HT(1Apl(b)) receptor and with activation of endogenous dopamine and FMRFamide receptors in sensory neurons. Pleural sensory neurons are heterogeneous for their inhibitory response to endogenous transmitters, with dopamine being the most prevalent, followed by FMRFamide, and only a small number of neurons with inhibitory responses to 5-HT. The inhibitory response is dominant, reduces membrane excitability and synaptic efficacy, and can reverse 5-HT facilitation at both naive and depressed synapses. Indeed, dopamine can reverse PKC translocation during the continued application of 5-HT. Reversal of translocation can also be seen after translocation mediated by an analog of diacylglycerol, suggesting inhibition is not through blockade of diacylglycerol production. The effects of inhibition on PKC translocation can be rescued by phosphatidic acid, consistent with the inhibitory response involving a reduction or block of production of this lipid. However, phosphatidic acid could not recover PKC-dependent synaptic facilitation due to an additional inhibitory effect on the non-L-type calcium flux linked to synaptic transmission. In summary, we find a novel mechanism downstream of inhibitory receptors linked to inhibition of PKC activation in Aplysia sensory neurons.
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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) | 0.002 | 0.001 |
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".