Differential induction of polar and non‐polar metabolism during wound‐induced suberization in potato (<i>Solanum tuberosum</i> L.) tubers
Bibliographic record
Abstract
Wound-induced suberin deposition involves the temporal and spatial coordination of phenolic and fatty acid metabolism. Phenolic metabolism leads to both soluble metabolites that accumulate as defense compounds as well as hydroxycinnamoyl derivatives that form the basis of the poly(phenolic) domain found in suberized tissue. Fatty acid metabolism involves the biosynthesis of very-long-chain fatty acids, 1-alkanols, ω-hydroxy fatty acids and α,ω-dioic acids that form a poly(aliphatic) domain, commonly referred to as suberin. Using the abscisic acid (ABA) biosynthesis inhibitor fluridone (FD), we reduced wound-induced de novo biosynthesis of ABA in potato tubers, and measured the impact on the expression of genes involved in phenolic metabolism (StPAL1, StC4H, StCCR, StTHT), aliphatic metabolism (StCYP86A33, StCYP86B12, StFAR3, StKCS6), metabolism linking phenolics and aliphatics (StFHT) or acyl chains and glycerol (StGPAT5, StGPAT6), and in the delivery of aliphatic monomers to the site of suberization (StABCG1). In FD-treated tissue, both aliphatic gene expression and accumulation of aliphatic suberin monomers were delayed. Exogenous ABA restored normal aliphatic suberin deposition in FD-treated tissue, and enhanced aliphatic gene expression and poly(aliphatic) domain deposition when applied alone. By contrast, phenolic metabolism genes were not affected by FD treatment, while FD + ABA and ABA treatments slightly enhanced the accumulation of polar metabolites. These data support a role for ABA in the differential induction of phenolic and aliphatic metabolism during wound-induced suberization in potato.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".