Hydrogen Peroxide Is Required for Poly(phenolic) Domain Formation during Wound-Induced Suberization
Bibliographic record
Abstract
The requirement for hydrogen peroxide (H 2 O 2 ) during suberization was demonstrated in wound-induced potato tubers by monitoring the extent of phenolic polymerization after the inhibition of H 2 O 2 production using diphenyleneiodonium (DPI). In DPI-treated tissues the extent of phenolic polymerization in suberized tissues, measured using DFRC (Derivatization Followed by Reductive Cleavage) and thioglycolic acid analyses, was greatly reduced relative to untreated controls. Concomitantly, a large quantity of new soluble phenolics accumulated in the DPI-treated tissue some of which were not present in the controls. We suggest that the inhibition of H 2 O 2 production prevented these phenolics from being oxidized by cell wall peroxidases. As a result, these phenolics were left unpolymerized and accumulated in the tissue. Several of the soluble phenolics were identified as hydroxycinnamic acid derivatives. From the data presented, it was concluded that H 2 O 2 is required for the polymerization step in the formation of the poly(phenolic) domain of suberized potato tubers. Keywords: Solanum tuberosum; Derivatization Followed by Reductive Cleavage (DFRC); diphenyleneiodonium; hydrogen peroxide; hydroxycinnamic acids; NADPH-dependent oxidase; poly(phenolic) domain; soluble phenolics; thioglycolic acid; wall-bound phenolics; wound-induced suberization
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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) | 0.001 | 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".