Pectinmethylesterases (PME) and Pectinmethylesterase Inhibitors (PMEI) Enriched during Phloem Fiber Development in Flax (Linum usitatissimum)
Bibliographic record
Abstract
Flax phloem fibers achieve their length by intrusive-diffusive growth, which requires them to penetrate the extracellular matrix of adjacent cells. Fiber elongation therefore involves extensive remodelling of cell walls and middle lamellae, including modifying the degree and pattern of methylesterification of galacturonic acid (GalA) residues of pectin. Pectin methylesterases (PME) are important enzymes for fiber elongation as they mediate the demethylesterification of GalA in muro, in either a block-wise fashion or in a random fashion. Our objective was to identify PMEs and PMEIs that mediate phloem fiber elongation in flax. For this purpose, we measured transcript abundance of candidate genes at nine different stages of stem and fiber development and found sets of genes enriched during fiber elongation and maturation as well as during xylem development. We expressed one of the flax PMEIs in E. coli and demonstrated that it was able to inhibit most of the native PME activity in the upper portion of the flax stem. These results identify key genetic components of the intrusive growth process and define targets for fiber engineering and crop improvement.
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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) | 0.000 | 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 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".