Neuroendocrine Control of Reproduction in<i>Aplysia</i>by the Bag Cell Neurons
Bibliographic record
Abstract
The bag cell neurons of Aplysia californica are a tractable preparation for the study of neuroendocrine cell function and hormone release. During a profound change in their electrical properties, known as the after-discharge, these neurons secrete egg-laying hormone (ELH) into the bloodstream to trigger reproductive behavior and propagation of the species. Following brief cholinergic synaptic input, bag cell neurons depolarize and undergo two phases of synchronized action potential firing. A fast phase, typified by bursting at ~5 Hz, usually lasts ~1 min and initiates multiple signaling cascades, such as Ca2+, cyclic AMP (cAMP), phosphatidyinositol turnover and increases in the activity of protein kinases A and C (PKA, PKC). A slow phase, in which bursting slows to ~1 Hz while second messengers gate multiple cationic currents, prolongs the depolarization that maintains firing for ~30 min. PKC both facilitates one of these cation channels and recruits a covert voltage-gated Ca2+ channel to the plasma membrane to promote exocytosis of ELH-containing dense core vesicles from axon terminals. The ELH secreted by bag cell neurons travels through the bloodstream to myocytes around the gonadal follicles, stimulating the ovotestis to release oocytes that are subsequently fertilized and extruded. The neurons also secrete additional peptides, termed bag cell peptides, some of which cause auto-excitatory feedback, while others assist with termination of the afterdischarge. Termination occurs as levels of cAMP and Ca2+ return to baseline, and inhibitory K+ currents are recruited to oppose spiking and repolarize the membrane to rest. However, ELH release by the neurons may continue after spiking has ceased, prolonging the action on the ovotestis and egg-laying behavior. The bag cell neurons are master switch neurons for reproductive behavior in Aplysia and share similarities with neuroendocrine cells of higher-order animals.
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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".