How the Anatomy of the Epidermal Cells Is Correlated to the Transient Response of Stomata
Bibliographic record
Abstract
Abstract Here, we show the possible correlation between the anatomical characteristics of epidermal cells of Arabidopsis thaliana with the stomata transient opening, which is commonly called the Wrong-Way Response (WWR). The WWR was induced by either reduced air humidity or leaf excision. Five genotypes of A. thaliana Col8, epf1epf2, lcd1-1 , SALK069, and UBP, respectively, with anatomical differences in epidermal cells such as stomatal density, stomata size, size, and shape of the pavement cells were selected. These genotypes allowed us to investigate the mutual effects of stomata density and size on WWR. Scanning Electron Microscopy (SEM) was applied for image acquisition of the abaxial and adaxial surface of the leaves and the main features of the epidermal cells were extracted by one of the additions to the MiToBo plugin of ImageJ/Fiji called PaCeQuant. The stomatal conductance to water vapor (gs) was measured using the portable photosynthesis measurement system LICor-6800. Our linear models showed that the size of the stomata explained the rate of WWR induced by reduced air humidity, so genotypes with smaller stomata showed a smaller rate of the WWR. After leaf excision, however, there was no correlation between the size of the stomata and the rate of the WWR. Moreover, we found that after both, reduced air humidity and leaf excision, the size of the pavement cells on the abaxial surface is correlated to the rate of the WWR; genotypes with smaller pavement cells on the abaxial surface had a smaller rate of WWR.
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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 | 0.001 |
| 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".