Separate Ca<sup>2+</sup>Sources Are Buffered by Distinct Ca<sup>2+</sup>Handling Systems in<i>Aplysia</i>Neuroendocrine Cells
Bibliographic record
Abstract
Although the contribution of Ca(2+) buffering systems can vary between neuronal types and cellular compartments, it is unknown whether distinct Ca(2+) sources within a neuron have different buffers. As individual Ca(2+) sources can have separate functions, we propose that each is handled by unique systems. Using Aplysia californica bag cell neurons, which initiate reproduction through an afterdischarge involving multiple Ca(2+)-dependent processes, we investigated the role of endoplasmic reticulum (ER) and mitochondrial sequestration, as well as extrusion via the plasma membrane Ca(2+)-ATPase (PMCA) and Na(+)/Ca(2+) exchanger, to the clearance of voltage-gated Ca(2+) influx, Ca(2+)-induced Ca(2+)-release (CICR), and store-operated Ca(2+) influx. Cultured bag cell neurons were filled with the Ca(2+) indicator, fura-PE3, to image Ca(2+) under whole-cell voltage clamp. A 5 Hz, 1 min train of depolarizing voltage steps elicited voltage-gated Ca(2+) influx followed by EGTA-sensitive CICR from the mitochondria. A compartment model of Ca(2+) indicated the effect of EGTA on CICR was due to buffering of released mitochondrial Ca(2+) rather than uptake competition. Removal of voltage-gated Ca(2+) influx was dominated by the mitochondria and PMCA, with no contribution from the Na(+)/Ca(2+) exchanger or sarcoplasmic/endoplasmic Ca(2+)-ATPase (SERCA). In contrast, CICR recovery was slowed by eliminating the Na(+)/Ca(2+) exchanger and PMCA. Last, store-operated influx, evoked by ER depletion, was removed by the SERCA and depended on the mitochondrial membrane potential. Our results demonstrate that distinct buffering systems are dedicated to particular Ca(2+) sources. In general, this may represent a means to differentially regulate Ca(2+)-dependent processes, and for Aplysia, influence how reproductive behavior is triggered.
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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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".