Composition differences between epicuticular and intracuticular wax substructures: How do plants seal their epidermal surfaces?
Bibliographic record
Abstract
The protective wax coating on plant surfaces has long been considered to be non-uniform in composition at a subcellular scale. In recent years, direct evidence has started to accumulate showing quantitative compositional differences between the epicuticular wax (i.e. wax exterior to cutin that can be mechanically peeled off) and intracuticular wax (i.e. wax residing within the mechanically resistant layer of cutin) layers in particular. This review provides a first synthesis of the results acquired for all the species investigated to date in order to assign chemical information directly to cuticle substructures, together with an overview of the methods used and a discussion of possible mechanisms and biological functions. The development of methods to probe the wax for z-direction heterogeneity began with differential solvent extractions. Further research employing mechanical wax removal by adhesives permitted the separation and analysis of the epicuticular and intracuticular wax. In wild-type plants, the intracuticular (1-30 μg cm(-2)) plus the epicuticular wax (5-30 μg cm(-2)) combined to a total of 8-40 μg cm(-2). Cyclic wax constituents, such as triterpenoids and alkylresorcinols, preferentially or entirely accumulate within the intracuticular layer. Within the very-long-chain aliphatic wax components, primary alcohols tend to accumulate to higher percentages in the intracuticular wax layer, while free fatty acids and alkanes in many cases accumulate in the epicuticular layer. Compounds with different chain lengths are typically distributed evenly between the layers. The mechanism causing the fractionation remains to be elucidated but it seems plausible that it involves, at least in part, spontaneous partitioning due to the physico-chemical properties of the wax compounds and interactions with the intracuticular polymers. The arrangement of compounds probably directly influences cuticular functions.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".