Inactivation of ICa-L is the major determinant of use-dependent facilitation in rat cardiomyocytes
Bibliographic record
Abstract
Two models have been proposed to explain facilitation of the L-type calcium current (I(Ca-L)). A positive feedback model proposes that calcium released during a conditioning pulse (I(1)) facilitates the subsequent pulse (I(2)) via calmodulin/calmodulin kinase II (CaMKII) mechanisms. The negative feedback model proposes that the calcium release of each pulse feeds back on itself via calcium-dependent inactivation. The relative physiological roles were evaluated in rat ventricular myocytes. Paired pulses (450 ms interpulse interval) elicited facilitation (I(2) of 872 ± 145 versus I(1) of 777 ± 132 pA, P < 0.01). Inactivation time (T(0.37)) was prolonged for I(2)versus I(1) (22 ± 2 and 16 ± 2 ms, P > 0.01). Evidence for the negative feedback mechanism includes: (a) ryanodine (0.3 mm) eliminated facilitation, surprisingly by increasing the amplitude of I(1) more than that of I(2) (1039 ± 216 and 977 ± 186 pA) and eliminated the difference in T(0.37) between I(2) and I(1) (33.1 ± 4.5 versus 32.5 ± 4.6 ms); (b) an outward I(2), which does not trigger sarcoplasmic reticulum (SR) Ca(2+) release, eliminated facilitation even when it was conditioned by an inward I(1); (c) facilitation decayed as the I(1)–I(2) interval lengthened (time constant (τ) = 16.9 ± 1.4 s); (d) thapsigargin (0.1 μm) slowed this decay (τ= 43.8 ± 11.7 s) whereas isoproterenol accelerated it (τ<= 5.6 ± 1.4 s, P < 0.01) and T(0.37) paralleled this decay; and (e) the magnitude of I(Ca-L) was negatively correlated with the sodium-calcium exchange current (I(Na/Ca)) elicited by the SR-Ca(2+) release. In conclusion, Ca(2+)-dependent inactivation of I(Ca-L) is the major mechanism underlying facilitation.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".