Novel control of lactate dehydrogenase from the freeze tolerant wood frog: role of posttranslational modifications
Bibliographic record
Abstract
Lactate dehydrogenase (LDH), the terminal enzyme of anaerobic glycolysis, plays a crucial role both in sustaining glycolytic ATP production under oxygen-limiting conditions and in facilitating the catabolism of accumulated lactate when stress conditions are relieved. In this study, the effects on LDH of in vivo freezing and dehydration stresses (both of which impose hypoxia/anoxia stress on tissues) were examined in skeletal muscle of the freeze-tolerant wood frog, Rana sylvatica. LDH from muscle of control, frozen and dehydrated wood frogs was purified to homogeneity in a two-step process. The kinetic properties and stability of purified LDH were analyzed, revealing no significant differences in V max, K m and I 50 values between control and frozen LDH. However, control and dehydrated LDH differed significantly in K m values for pyruvate, lactate, and NAD, I 50 urea, and in temperature, glucose, and urea effects on these parameters. The possibility that posttranslational modification of LDH was responsible for the stable differences in enzyme behavior between control and dehydrated states was assessed using ProQ diamond staining to detect phosphorylation and immunoblotting to detect acetylation, methylation, ubiquitination, SUMOylation and nitrosylation of the enzyme. LDH from muscle of dehydrated wood frogs showed significantly lower levels of acetylation, providing one of the first demonstrations of a potential role for protein acetylation in the stress-responsive control of a metabolic enzyme.
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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) | 0.001 | 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".