G-proteins modulate invertebrate synaptic calcium channel (LCav2) differently from the classical voltage-dependent regulation of mammalian Cav2.1 and Cav2.2 channels
Bibliographic record
Abstract
Voltage-gated calcium channels in the Ca(v)2 channel class are regulators of synaptic transmission and are highly modified by transmitter inputs that activate synaptic G-protein-coupled receptors (GPCRs). A ubiquitous form of G-protein modulation involves an inhibition of mammalian Ca(v)2.1 and Ca(v)2.2 channels by Gbetagamma dimers that can be relieved by high-frequency trains of action potentials. Here, we address whether the ubiquitous and versatile form of G-protein regulation in mammals is also found in simpler invertebrate nervous systems. Remarkably, the invertebrate LCa(v)2 channel from the pond snail, Lymnaea stagnalis, does not bear any of the hallmarks of mammalian, voltage-dependent G-protein inhibition of Ca(v)2.2. Swapping either the I-II linker or N-terminus of Ca(v)2.2, which serve as key binding domains for G-protein inhibition, does not endow invertebrate LCa(v)2 channels with voltage-dependent G-protein modulatory capacity. Instead, in vitro expressed LCa(v)2 channels are inhibited slowly by the activation of cAMP, in a manner that depends on G-proteins but does not depend on Gbetagamma subunits. A similar G-protein and cAMP-dependent inhibition of nifedipine-insensitive LCa(v)2 currents is also consistent in native and identified Lymnaea VD4 neurons. The slower inhibition using a cellular messenger such as cAMP may meet the modulatory needs in invertebrates while an activity-dependent regulation, evolving in vertebrates, provides a more dynamic, fine-tuning of neurosecretion by regulating the influence of neurotransmitter inputs through presynaptic GPCRs.
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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) | 0.001 | 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".