Plant cell walls as mechanical signaling hubs for morphogenesis
Bibliographic record
Abstract
The instructive role of mechanical cues during morphogenesis is increasingly being recognized in all kingdoms. Patterns of mechanical stress depend on shape, growth and external factors. In plants, the cell wall integrates these three parameters to function as a hub for mechanical feedback. Plant cells are interconnected by cell walls that provide structural integrity and yet are flexible enough to act as both targets and transducers of mechanical cues. Such cues may act locally at the subcellular level or across entire tissues, requiring tight control of both cell-wall composition and cell-cell adhesion. Here we focus on how changes in cell-wall chemistry and mechanics act in communicating diverse cues to direct growth asymmetries required for plant morphogenesis. We explore the role of cellulose microfibrils, microtubule arrays and pectin methylesterification in the transduction of mechanical cues during morphogenesis. Plant hormones can affect the mechanochemical composition of the cell wall and, in turn, the cell wall can modulate hormone signaling pathways, as well as the tissue-level distribution of these hormones. This also leads us to revisit the position of biochemical growth factors, such as plant hormones, acting both upstream and downstream of mechanical signaling. Finally, while the structure of the cell wall is being elucidated with increasing precision, existing data clearly show that the integration of genetic, biochemical and theoretical studies will be essential for a better understanding of the role of the cell wall as a hub for the mechanical control of plant morphogenesis.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".