Theory and applications of geometric scaling of localized calcium release events
Bibliographic record
Abstract
Geometric measures of localized calcium release (LCR) events have been used to understand their biophysical basis. We found power law scaling between three such metrics-maximum amplitude (MA), mass above half-maximum amplitude (MHM), and area at half-maximum amplitude (AHM). In an effort to understand this scaling a minimal analytic model was employed to simulate LCR events recorded by confocal line scan. The distribution of logMHM as a function of logAHM, pMHM(pAHM), was dependent on model parameters such as channel open time, current size, line scan offset, and apparent diffusion coefficient. The distribution of log[MHM/AHM] as a function of logMA, p[MHM/AHM](pMA), was invariant, reflecting the gross geometry of the LCR event. The findings of the model were applied to real LCR line scan data from rabbit portal vein myocytes, rat cerebral artery myocytes, and guinea pig fundus knurled cells. pMHM(pAHM) could be used to distinguish two populations of LCR events in portal vein, even at the scale of "calcium noise," and to calculate the relative current of the two. The relative current was 2. pMHM(pAHM) could also be used to study pharmacological effects. The pMHM(pAHM) distribution of knurled cell LCR events was markedly contracted by ryanodine, suggesting a reduction in channel open time. The p[MHM/AHM](pMA) distributions were invariant across all cell types and were consistent with the model, underlying the common physical basis of their geometry. The geometric scaling of LCR events demonstrated here may help with their mechanistic characterization.
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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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".