Effects of seasonal change and prolonged anoxia on metabolic enzymes of <i>Littorina littorea</i>
Bibliographic record
Abstract
The effects of seasonal change (July versus November) and prolonged anoxia (N2 atmosphere at 5 or 10°C for 6 days) exposure in vivo on the activities of 18 enzymes, as well as the kinetic properties of phosphofructokinase (PFK) and pyruvate kinase (PK), were investigated in foot muscle and digestive gland of the marine periwinkle Littorina littorea L. Seasonal differences in enzyme maximal activities were tissue-specific, with generally increased activities during the summer and changes in a greater number of enzymes in digestive gland than in foot muscle. Seasonal differences in the kinetic properties of PFK and PK were observed in both tissues. PK from digestive gland of winter animals showed a much higher S0.5 for phosphoenolpyruvate and stronger changes in enzyme kinetic properties in response to anoxia than did the enzyme in summer animals; this may suggest the presence of seasonal isozymes. The effects of anoxia were tissue- and season-specific. Anoxia exposure during the winter induced a greater number of changes in enzyme maximal activities in foot muscle than in digestive gland. Anoxia-induced changes in the kinetic properties of both PFK and PK were also seen in both organs. For PK, these changes were consistent with less active enzyme forms in the anoxic state. Hence, both seasonal and environmental (anoxia) factors influence enzyme maximal activities and kinetic properties in L. littorea.
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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".