Integrated response of antioxidant biomarkers in the liver and white muscle of European hake (Merluccius merluccius L.) females from the Adriatic sea with respect to environmental influences
Bibliographic record
Abstract
We investigated the integrated response of antioxidant defense enzymes (total superoxide dismutase (TotSOD), manganese-containing superoxide dismutase (MnSOD), copper-zinc-containing superoxide dismutase (CuZnSOD), catalase (CAT), glutathione peroxidase (GSH-Px), glutathione reductase (GR) and phase II biotransformation enzyme, glutathione- S-transferase (GST)) in the liver and white muscle of females of European hake (Merluccius merluccius L.) from the Adriatic Sea (Montenegro) in winter and spring. The activity of GSH-Px in the liver was significantly increased, while GST activity was decreased in spring compared to the winter. In white muscle, the activities of TotSOD and CuZnSOD were increased, while the activities of MnSOD, CAT, GSH-Px, GR and GST were decreased in spring when compared to the matching values in winter. The activities of TotSOD and CuZnSOD in winter were markedly lower in the muscle than in the liver, while the activity of MnSOD in the muscle was higher when compared to the liver. Principal component analysis (PCA) revealed clear separation of the investigated antioxidant biomarkers between tissues and seasons, while the integrated biomarker response (IBR) showed that the most intensive antioxidant biomarker response was in the liver in spring. Star plots of IBR showed a dominant contribution of glutathione-dependent biomarkers (GSH-Px, GR and GST) and CAT in both tissues and seasons with respect to SOD isoenzymes. All enzyme activities (except MnSOD) were greater in the liver in comparison to the white muscle. Our results show that the liver possesses a greater capacity to establish and maintain homeostasis under changing environmental conditions in winter and spring. At the same time, seasonal effects are more pronounced in muscle tissue.
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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".