Oxidative stress response of <i>Mycosphaerella fijiensis</i>, the causal agent of black leaf streak disease in banana plants, to hydrogen peroxide and paraquat
Bibliographic record
Abstract
Mycosphaerella fijiensis causes black leaf streak disease in banana and plantain. This fungus is usually attacked by reactive oxygen species secreted by the plant or during exposure to fungicide, however, little is known about the antioxidant response of the fungus. In this study, mycelia were observed to totally decompose 30 mmol/L of hydrogen peroxide (H2O2) within 120 min, liberating oxygen bubbles, and also to survive in concentrations as high as 100 mmol/L H2O2. The oxidative stress responses to H2O2, paraquat, and hydroquinone were characterized in terms of the activities of catalase and superoxide dismutase (SOD). Two active catalase bands were seen in native PAGE induced by H2O2. Band I had monofunctional activity and band II had bifunctional catalase-peroxidase activity. Two isozymes of SOD, distinguishable by their cyanide sensitivity, were found; CuZnSOD was the main one. The combination of H2O2 and 3-aminotriazole reduced the accumulation of biomass up to 40% compared with exposure to H2O2 alone, suggesting that catalase is important for the rapid decomposition of H2O2 and has a direct bearing on cell viability. The results also suggest that the superoxide anion formed through the redox of paraquat and hydroquinone has a greater effect than H2O2 on the cellular viability of M. fijiensis.
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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".