Ca <sup>2+</sup> Sparks and Waves in Canine Purkinje Cells
Bibliographic record
Abstract
We have investigated the subcellular spontaneous Ca2+ events in canine Purkinje cells using laser scanning confocal microscopy. Three types of Ca2+ transient were found: (1) nonpropagating Ca2+ transients that originate directly under the sarcolemma and lead to (2) small Ca2+ wavelets in a region limited to 6-microm depth under the sarcolemma causing (3) large Ca2+ waves that travel throughout the cell (CWWs). Immunocytochemical studies revealed 3 layers of Ca2+ channels: (1) channels associated with type 1 IP3 receptors (IP3R1) and type 3 ryanodine receptors (RyR3) are prominent directly under the sarcolemma; (2) type 2 ryanodine receptors (RyR2s) are present throughout the cell but virtually absent in a layer between 2 and 4 microm below the sarcolemma (Sub-SL); (3) type 3 ryanodine receptors (RyR3) is the dominant Ca2+ release channel in the Sub-SL. Simulations of both nonpropagating and propagating transients show that the generators of Ca2+ wavelets differ from those of the CWWs with the threshold of the former being less than that of the latter. Thus, Purkinje cells contain a functional and structural Ca2+ system responsible for the mechanism that translates Ca2+ release occurring directly under the sarcolemma into rapid Ca2+ release in the Sub-SL, which then initiates large-amplitude long lasting Ca2+ releases underlying CWWs. The sequence of spontaneous diastolic Ca2+ transients that starts directly under the sarcolemma and leads to Ca2+ wavelets and CWWs is important because CWWs have been shown to cause nondriven electrical activity.
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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".