Mechanical stress initiates and sustains the morphogenesis of wavy leaf epidermal cells
Bibliographic record
Abstract
Plant cell morphogenesis is governed by the mechanical properties of the cell wall and the resulting cell shape is intimately related to the respective specific function. Pavement cells covering the surface of plant leaves form wavy interlocking patterns in many plants. We use computational mechanics to simulate the morphogenetic process based on experimentally assessed cell shapes, growth dynamics, and cell wall chemistry. The simulations and experimental evidence suggest a multistep process underlying the morphogenesis of pavement cells during tissue differentiation. The mechanical shaping process relies on spatially confined, feedback-augmented stiffening of the cell wall in the periclinal walls, an effect that correlates with experimentally observed deposition patterns of cellulose and de-esterified pectin. We provide evidence for mechanical buckling of the pavement cell walls that can robustly initiate patterns de novo and may precede chemical and geometrical anisotropy. Highlights A multistep mechano-chemical morphogenetic process underlies the wavy pattern of epidermal pavement cells. Microtubule polarization is preceded by an event that breaks mechanical isotropy in the cell wall. Mechanical models simulate the formation of wavy cell shapes, predict buckling of the cell walls and spatially confined variations in the mechanical properties of leaf epidermal cells. Stress/strain stiffening following the buckling of the cell walls constitutes a crucial element in a positive feedback loop forming interlocking pavement cells. Polarization of cortical microtubules, cellulose microfibrils, and de-esterified pectin occur at the necks of wavy pavement cells, matching the in silico prediction of cell wall stiffening.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".