Effect of Temperature and the F27W Mutation on the Ca<sup>2+</sup> Activated Structural Transition of Trout Cardiac Troponin C
Bibliographic record
Abstract
The Ca(2+) sensitivity of cardiac contractile element is reduced at lower temperatures, in contrast to that in fast skeletal muscle. Cardiac troponin C (cTnC) replacement in mammalian skinned fibers showed that TnC plays a critical role in this phenomenon (Harrison and Bers, (1990), Am. J. Physiol. 258, C282-8). Understanding the differences in affinity and structure between cTnCs from cold-adapted ectothermic species and mammals may bring new insights into how the different isoforms provide different resistances to cold. We followed the Ca(2+) titration to the regulatory domain of rainbow trout cTnC by NMR (wild type at 7 and 30 degrees C and F27W mutant at 30 degrees C) and fluorescence (F27W mutant, at 7 and 30 degrees C) spectroscopies. Using NMR spectroscopy, we detected Ca(2+) binding to site I of trout cTnC at high concentrations. This places trout cTnC between mammalian cTnC, in which site I is completely inactive, and skeletal TnC, in which site I binds Ca(2+) during muscle activation, and which is not as much affected by lower temperatures. This binding was seen both at 7 and at 30 degrees C. Despite the low Ca(2+) affinity, trout TnC site I may increase the likelihood of an opening of the regulatory domain, thus increasing the affinity for TnI. This way, it may be responsible for trout cTnC's capacity to function at lower temperatures.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".