Regulation of an<i>Aplysia</i>Bag Cell Neuron Cation Channel by Closely Associated Protein Kinase A and a Protein Phosphatase
Bibliographic record
Abstract
Ion channel regulation by closely associated kinases or phosphatases has emerged as a key mechanism for orchestrating neuromodulation. An exemplary case is the nonselective cation channel that drives the afterdischarge in Aplysia bag cell neurons. Initial studies showed that this channel is modulated by both a closely associated PKC and a serine/threonine protein phosphatase (PP). In excised, inside-out patches, the addition of ATP (a phosphate source) increases open probability (P(O)) through PKC, and this is reversed by the PP. Previous work also reported that, in certain cases, ATP can decrease cation channel P(O). The present study characterizes and provides a mechanism for this decreased P(O) ATP response. The kinetic change for channels inhibited by ATP was identical to the previously reported effect of exogenously applied protein kinase A (PKA) (i.e., a lengthening of the third closed-state time constant). The decreased P(O) ATP response was blocked by the PKA inhibitor peptide PKA(6-22), and its reversal was prevented by the PP inhibitor microcystin-LR. Furthermore, PKA(6-22) did not alter the increased P(O) ATP response. This suggests that both PKA and a PP are closely associated with these cation channels, but PKA and PKC are not simultaneously targeted. After an afterdischarge, the bag cell neurons are refractory and fail to respond to subsequent stimulation. The association of PKA with the cation channel may contribute to this decrease in excitability. Altering the constituents of a regulatory complex, such as exchanging PKA for PKC, may represent a general mechanism to precisely control ion channel function and excitability.
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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".