Ca<sup>2+</sup>-Induced Ca<sup>2+</sup>Release in<i>Aplysia</i>Bag Cell Neurons Requires Interaction Between Mitochondrial and Endoplasmic Reticulum Stores
Bibliographic record
Abstract
Intracellular Ca2+ is influenced by both Ca2+ influx and release. We examined intracellular Ca2+ following action potential firing in the bag cell neurons of Aplysia californica. Following brief synaptic input, these neuroendocrine cells undergo an afterdischarge, resulting in elevated Ca2+ and the secretion of neuropeptides to initiate reproduction. Cultured bag cell neurons were injected with the Ca2+ indicator, fura-PE3, and subjected to simultaneous imaging and electrophysiology. Delivery of a 5-Hz, 1-min train of action potentials (mimicking the fast phase of the afterdischarge) produced a Ca2+ rise that markedly outlasted the initial influx, consistent with Ca2+-induced Ca2+ release (CICR). This response was attenuated by about half with ryanodine or depletion of the endoplasmic reticulum (ER) by cyclopiazonic acid. However, depletion of the mitochondria, with carbonyl cyanide 4-(trifluoromethoxy) phenylhydrazone, essentially eliminated CICR. Dual depletion of the ER and mitochondria did not reduce CICR further than depletion of the mitochondria alone. Moreover, tetraphenylphosphonium, a blocker of mitochondrial Ca2+ release, largely prevented CICR. The Ca2+ elevation during and subsequent to a stimulus mimicking the full afterdischarge was prominent and enhanced by protein kinase C activation. Traditionally, the ER is seen as the primary Ca2+ source for CICR. However, bag cell neuron CICR represents a departure from this view in that it relies on store interaction, where Ca2+ released from the mitochondria may in turn liberate Ca2+ from the ER. This unique form of CICR may be used by both bag cell neurons, and other neurons, to initiate secretion, activate channels, or induce gene expression.
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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".