Activity-Dependent Regulation of Neurohormone Synthesis and Its Impact on Reproductive Behavior in Aplysia1
Bibliographic record
Abstract
The bag cell neurons (BCNs) of the mollusk Aplysia californica provide a simple model system for investigating cellular and molecular events regulating synthesis and secretion of a reproductive neuropeptide and their impact on physiology and behavior. The BCNs secrete a large amount of egg-laying hormone (ELH) in response to an electrical afterdischarge. The afterdischarge also triggers cellular and molecular events leading to upregulation of ELH biosynthesis to replenish the supply of releasable hormone that was lost because of secretion. In the present review, we discuss signal-transduction events that link membrane excitability to ELH biosynthesis. We present evidence that the afterdischarge stimulates ELH synthesis by upregulating translation of ELH mRNA rather than by activating ELH gene transcription. This increase in ELH synthesis is accompanied by a decrease in total protein synthesis, suggesting that the synthetic machinery is being funneled selectively toward ELH. We also discuss work showing that afterdischarge-induced ELH synthesis uses a novel mechanism of translation initiation, one involving a switch from cap-dependent to cap-independent translation initiation that activates an internal ribosome entry site (IRES) located in the 5'-untranslated region of ELH mRNA. The IRES-regulated translation provides a unique cellular mechanism to selectively upregulate synthesis of a critical reproductive hormone at the expense of nonessential proteins.
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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) | 0.000 | 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".