Cuticular Lipid Composition, Surface Structure, and Gene Expression in Arabidopsis Stem Epidermis
Bibliographic record
Abstract
All vascular plants are protected from the environment by a cuticle, a lipophilic layer synthesized by epidermal cells and composed of a cutin polymer matrix and waxes. The mechanism by which epidermal cells accumulate and assemble cuticle components in rapidly expanding organs is largely unknown. We have begun to address this question by analyzing the lipid compositional variance, the surface micromorphology, and the transcriptome of epidermal cells in elongating Arabidopsis (Arabidopsis thaliana) stems. The rate of cell elongation is maximal near the apical meristem and decreases steeply toward the middle of the stem, where it is 10 times slower. During and after this elongation, the cuticular wax load and composition remain remarkably constant (32 microg/cm2), indicating that the biosynthetic flux into waxes is closely matched to surface area expansion. By contrast, the load of polyester monomers per unit surface area decreases more than 2-fold from the upper (8 microg/cm2) to the lower (3 microg/cm2) portion of the stem, although the compositional variance is minor. To aid identification of proteins involved in the biosynthesis of waxes and cutin, we have isolated epidermal peels from Arabidopsis stems and determined transcript profiles in both rapidly expanding and nonexpanding cells. This transcriptome analysis was validated by the correct classification of known epidermis-specific genes. The 15% transcripts preferentially expressed in the epidermis were enriched in genes encoding proteins predicted to be membrane associated and involved in lipid metabolism. An analysis of the lipid-related subset is presented.
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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) | 0.001 | 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".