Timing Is Everything: The Metabolic Partitioning of Suberin-Destined Carbon
Bibliographic record
Abstract
Suberin is a cell wall-associated biopolymer that possesses both poly(phenolic) and poly(aliphatic) elements assembled into chemically and spatially distinct domains. Domain-specific monomers are formed via a branched pathway between phenolic and aliphatic metabolisms. Previous transcript accumulation data (RNAseq) from early stages of wound-induced suberization revealed highly coordinated, temporal changes in the regulation of these two branches. Notably, phenolic metabolism-associated transcripts accumulated first, indicating a preference toward phenolic production early on post-wounding. To better understand the dynamics of suberin monomer biosynthesis and assembly, we assessed carbon allocation between phenolic and aliphatic metabolisms during wound-induced suberization. To do so, [13C6]-glucose was administered to wound-healing potato tuber discs at different times post-wounding, and patterns of heavy carbon incorporation into (1) primary metabolites and (2) the suberin polymer were assessed. During early stages of wound-healing, carbon from glucose was rapidly incorporated into phenolic-destined metabolites, while at later stages it was shared between phenolic- and aliphatic-destined metabolites. Similarly, the pattern of labelled carbon incorporation into the poly(aliphatic) domain reflected a greater dedication of carbon towards 18:1 w-hydroxy fatty acid and 18:1 dioic acid (the two most abundant aliphatic monomers in potato suberin) later in the wound healing time course.
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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 | 0.001 | 0.001 |
| 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".