The effects of Cd on lipid peroxidation, hydrogen peroxide content and antioxidant enzyme activities in Cd-sensitive mutant rice seedlings
Bibliographic record
Abstract
Cadmium-sensitive rice (Oryza sativa L. subsp. Japonica ‘Zhonghua11’) mutants were obtained using an Agrobacterium tumefaciens-based gene delivery system. Significant phenotypic differences were observed between a Cd-sensitive mutant (ST) and wild type (WT) rice seedlings. Results indicated that Cd accumulation in the leaves of the mutant was twice that of the wild type after 10 d of 0.5 mM Cd2+ treatment. Furthermore, a rapid Cd-induced H2O2 increase was observed in the mutant leaves, which induced abnormally early activity in antioxidant enzymes such as superoxide dismutase (SOD). However, the mutant leaves showed lower catalase (CAT) activity. By contrast, guaiacol peroxidase (G-POD) activities were higher in the mutant than in the wild type roots. Together with the Cd toxicity-induced decline of early responsive enzymatic activities in vivo, especially CAT, the inability of mutants to scavenge accumulated H2O2 resulted in higher lipid peroxide levels. H2O2 might also strengthen the expression of G-POD as a signaling molecule. Results suggest that G-POD activity can be a potential biomarker reflecting Cd sensitivity in rice seedlings. Key words: Antioxidant enzyme, Cd toxicity, Cd-sensitive mutant, lipid peroxidation, rice (Oryza sativa L.)
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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) | 0.001 | 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) | 0.001 | 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".