Leaf cuticular lipids on the Shandong and Yukon ecotypes of saltwater cress, <i>Eutrema salsugineum</i>, and their response to water deficiency and impact on cuticle permeability
Bibliographic record
Abstract
The impact of water-deficit stress on leaf cuticular waxes and cutin monomers, and traits associated with cuticle permeability were examined in Shandong and Yukon ecotypes of Eutrema salsugineum (syn. Thellungiella salsuginea). Although Shandong exhibits glaucous leaves, and Yukon is non-glaucous, wax amounts on non-stressed Yukon leaves were 4.6-fold higher than on Shandong, due mainly to Yukon's eightfold higher wax fatty acids, especially the C22 and C24 acid homologues. Water deficit caused a 26.9% increase in total waxes on Shandong leaves, due mainly to increased C22 and C24 acids; and caused 10.2% more wax on Yukon, due mainly to an increase in wax alkanes. Total cutin monomers on non-stressed leaves of Yukon were 58.3% higher than on Shandong. Water deficit caused a 28.2% increase in total cutin monomers on Shandong, whereas total cutin monomers were not induced on Yukon. With or without stress, more abundant cuticle lipids were generally associated with lower water loss rates, lower chlorophyll efflux rates and an extended time before water deficit-induced wilting. In response to water deficit, Shandong showed elevated transcription of genes encoding elongase subunits, consistent with the higher stress induction of acids by Shandong. Yukon's higher induction of CER1 and CER3 transcripts may explain why alkanes increased most on Yukon after water deficit. Eutrema, with its diverse cuticle lipids and responsiveness, provides a valuable genetic resource for identifying new genes and alleles effecting cuticle metabolism, and lays groundwork for studies of the cuticle's role in extreme stress tolerance.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".