Antioxidant enzyme protein content in lean and obese women prior to and following a 12‐week endurance training protocol
Bibliographic record
Abstract
We investigated the interactive influence of obesity and endurance exercise training on the anti‐oxidant enzyme capacity in 24 (12 obese) women. Muscle biopsies were taken prior to and following a 12‐week progressive endurance exercise training protocol. CuZnSOD, MnSOD and catalase protein content were determined using Western blot analysis. CS and COX enzyme activities were determined using spectrophotometry. Prior to training, MnSOD, CuZnSOD and catalase protein content were similar for both groups. Training decreased CuZnSOD in obese women (P = 0.04). Correlational analyses revealed that the change in % body fat (BF) was negatively correlated with the change in CuZnSOD (r = −0.44, P = 0.04), and positively correlated with the change in MnSOD (r = 0.45, P = 0.04). In obese women, %BF was positively correlated with catalase at baseline (r = 0.73, P = 0.02), whereas in lean women baseline % BF was positively correlated with the change in catalase (r = 0.63, P = 0.03). CS and COX enzyme activity were similar in both groups prior to training, and training increased CS and COX (P < 0.001) enzyme activity in both groups. There was no correlation between CS or COX and the antioxidant enzymes. The primary cellular superoxide dismutases respond differently to a change in % BF induced by endurance exercise and may be indicative of the source of oxidative stress. The lack of correlation between mitochondrial function and antioxidant defense enzymes indirectly implies that mitochondrial sources of radical production may not contribute significantly to obesity related pathologies. (Supported by CIHR, Canada).
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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 | 0.001 |
| 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".