HSP70 Abundance and Antioxidant Capacity in Feeding and Fasting Gray Seal Pups: Suckling Is Associated with Higher Levels of Key Cellular Defenses
Bibliographic record
Abstract
Heat shock proteins (HSPs) and antioxidants are key cellular defenses against stress. Seals routinely undergo protracted fasting, which is normally associated with physiological stress in other animals. We tested the hypotheses that (1) relative HSP70 protein abundance is higher in liver and blubber of fasting relative to suckling wild gray seal pups; (2) differences in HSP70 are mirrored in tissue superoxide dismutase (SOD) and catalase activity, as well as glutathione levels; (3) extracellular HSP70 correlates with hepatic and blubber HSP70 abundance; and (4) protein carbonylation, an index of oxidative damage, is lower in tissues with higher levels of these cellular stress markers. In contrast to our expectation, suckling pups had higher relative HSP70 abundance and glutathione levels in liver and blubber and higher hepatic catalase activity. Plasma HSP70 did not correlate with liver or blubber abundance of the protein. Suckling pups did not experience greater protein carbonylation, suggesting that cellular protective mechanisms prevent protein damage despite an apparent increase in cellular stress. SOD activity was not affected by nutritional state, but in blubber tissue, it was positively correlated with blubber thickness. Greater requirements for antioxidants and HSPs in suckling pups or in animals with thicker blubber could arise from rapid protein synthesis, high metabolic fuel availability, and/or exposure to lipophilic toxins. Developmental and nutritional changes in cellular defenses have important implications for gray seals' susceptibility to additional stress exposure.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".