Regulation of sarcoendoplasmic reticulum Ca2+-ATPase (SERCA) in turtle muscle and liver during acute exposure to anoxia
Bibliographic record
Abstract
The freshwater turtle Trachemys scripta elegans naturally tolerates extended periods of anoxia during winter hibernation at the bottom of ice-locked ponds. Survival in this anoxic state is facilitated by a profound depression of metabolic rate. As calcium levels are known to be elevated in anoxic turtles, and ion pumping is an ATP-expensive process, we proposed that activity of the sarcoendoplasmic reticulum Ca(2+)-ATPase (SERCA) would be reduced in muscle and liver of T. s. elegans during acute (up to 20 h) exposure to anoxia. SERCA activity decreased approximately 30% in liver and approximately 40% in muscle after 1 h anoxia exposure and was approximately 50% lower after 20 h of anoxia exposure in both tissues, even though SERCA protein levels did not change. SERCA kinetic parameters (increased substrate K(m) values, increased Arrhenius activation energy) were indicative of a less active enzyme form under anoxic conditions. Interestingly, the less active SERCA in anoxic turtles featured greater stability than the enzyme from normoxic animals as determined by both kinetic analysis (effect of low pH and low temperatures on K(m) MgATP) and conformational resistance to urea denaturation. The quick time course of deactivation and the stable changes in kinetic parameters that resulted suggested that SERCA was regulated by a post-translational mechanism. In vitro experiments indicated that SERCA activity could be blunted by protein phosphorylation and enhanced by dephosphorylation in a tissue-specific manner.
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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".