Roles of Ca<sup>2+</sup>and protein kinase C in the excitatory response to serotonin in embryonic molluscan ciliary cells
Bibliographic record
Abstract
We examined the roles of Ca2+ and protein kinase C (PKC) in the cilio-excitatory response to serotonin in pedal ciliary cells from Helisoma trivolvis embryos. Serotonin (5-hydroxytryptamine; 5-HT; 100 micromol/L) induced an increase in ciliary beat frequency (CBF) was abolished by microinjected BAPTA (50 mmol/L), but was only partially inhibited by the phospholipase C inhibitor U-73122 (10 micromol/L). The diacylglycerol analogs 1-oleoyl-2-acetyl-sn-glycerol (100 micromol/L) and 1,2-dioctanoyl-sn-glycerol (100 micromol/L) caused increases in [Ca2+]i that were smaller than those induced by serotonin. In the absence of extracellular Ca2+, 1,2-dioctanoyl-sn-glycerol (100 micromol/L) failed to elicit an increase in both CBF and [Ca2+]i. In contrast, the serotonin-induced increase in CBF persisted in the absence of extracellular Ca2+, although the increase in [Ca2+]i was abolished. PKC inhibitors bisindolylmaleimide (10 and 100 nmol/L) and calphostin C (10 nmol/L) partially inhibited the serotonin-induced increase in CBF, but didn't affect the serotonin-induced change in [Ca2+]i. These findings suggest that an intracellular store-dependent increase in [Ca2+]i mediates the cilio-excitatory response to serotonin. Furthermore, although PKC is able to cause an increase in [Ca2+]i through calcium influx, it contributes to the cilio-excitatory response to 5-HT through a different mechanism.
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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 | 0.001 | 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".