Polar auxin transport modulates early leaf flattening
Bibliographic record
Abstract
The flattened leaf form is an important adaptation for efficient photosynthesis, and the developmental process of flattened leaves has been intensively studied. Classic microsurgery studies in potato and tomato suggest that the shoot apical meristem (SAM) communicates with the leaf primordia to promote leaf blade formation. More recently, it was found that polar auxin transport (PAT) could mediate this communication. However, it is unclear how the expression of leaf patterning genes is tailored by PAT routes originating from SAM. By combining experimental observations and computer model simulations, we show that microsurgical incisions and local inhibition of PAT in tomato interfere with auxin transport toward the leaf margins, reducing auxin response levels and altering the leaf blade shape. Importantly, oval auxin responses result in the bipolar expression of SlLAM1 that determines leaf blade formation. Furthermore, wounding caused by incisions promotes degradation of SlREV, a known regulator of leaf polarity. Additionally, computer simulations suggest that local auxin biosynthesis in early leaf primordia could remove necessity for external auxin supply originating from SAM, potentially explaining differences between species. Together, our findings establish how PAT near emerging leaf primordia determines spatial auxin patterning and refines SlLAM1 expression in the leaf margins to guide leaf flattening.
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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".