Author response: Why plants make puzzle cells, and how their shape emerges
Bibliographic record
Abstract
Cells with complex interlocking shapes, similar to pieces of a jigsaw puzzle, cover the surface of many leaves. Why do these curious shapes form, and what benefit do they provide to the plant? Plant cells are like small balloons surrounded by a strong cell wall. Their internal pressure can be higher than the pressure in a car tire. It is this pressure that gives non-woody plant tissue its shape. Take away the pressure, and the plant wilts. The pressure inside a cell creates a lot of mechanical stress on the epidermal cell walls – those that make up the surface of the plant. The extent of the stress depends on the shape and size of the cells; for example, large cells bulge out and experience more stress than small cells. This could mean that the shape of puzzle cells is an adaptation used by plants to reduce the stress on their surface. To investigate this possibility, Sapala, Runions et al. developed a computer simulation that models how a plant grows and re-creates a variety of realistic puzzle cell shapes. The simulations show that ‘paving’ the leaf surface with puzzle shaped cells instead of more regularly shaped cells reduces the stress in the epidermal cell walls. Counterintuitively, the simulations also show that complex puzzle shapes develop in parts of the plant that grow isotropically (uniformly in all directions), such as leaves. If a plant organ grows mostly in one direction, like in a root or stem, long thin cells are sufficient to reduce the stress on the epidermal cell wall. Sapala, Runions et al. tested this idea by analyzing the shape of organs and cells in many plant species and by genetically modifying growth directions in Arabidopsis thaliana plants. This confirmed that puzzle cell shape is related to both organ shape and how isotropically the plant grows. It had previously been proposed that mobile chemical signals passed between cells coordinate the process by which a lobe in one puzzle cell matches an indentation in its neighbor. However, the model developed by Sapala, Runions et al. does not require such chemical signaling. Instead, mechanical forces and the shape the puzzle cells themselves may transmit this information. Mechanical forces are known to have important effects on the shape and behavior of cells from other species too. For example, animal cells can develop into different cell types depending on the stiffness of the surface they are placed on. Now that Sapala, Runions et al. have highlighted that plant cell shapes also adapt to mechanical forces, further research is needed to uncover how these forces are sensed.
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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 | 0.002 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.014 | 0.009 |
| Insufficient payload (model declined to judge) | 0.111 | 0.038 |
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".