Immunoprofiling reveals unique cell‐specific patterns of wall epitopes in the expanding Arabidopsis stem
Bibliographic record
Abstract
The Arabidopsis inflorescence stem undergoes rapid directional growth, requiring massive axial cell-wall extension in all its tissues, but, at maturity, these tissues are composed of cell types that exhibit markedly different cell-wall structures. It is not clear whether the cell-wall compositions of these cell types diverge rapidly following axial growth cessation, or whether compositional divergence occurs at earlier stages in differentiation, despite the common requirement for cell-wall extensibility. To examine this question, seven cell types were assayed for the abundance and distribution of 18 major cell-wall glycan classes at three developmental stages along the developing inflorescence stem, using a high-throughput immunolabelling strategy. These stages represent a phase of juvenile growth, a phase displaying the maximum rate of stem extension, and a phase in which extension growth is ceasing. The immunolabelling patterns detected demonstrate that the cell-wall composition of most stem tissues undergoes pronounced changes both during and after rapid extension growth. Hierarchical clustering of the immunolabelling signals identified cell-specific binding patterns for some antibodies, including a sub-group of arabinogalactan side chain-directed antibodies whose epitope targets are specifically associated with the inter-fascicular fibre region during the rapid cell expansion phase. The data reveal dynamic, cell type-specific changes in cell-wall chemistry across diverse cell types during cell-wall expansion and maturation in the Arabidopsis inflorescence stem, and highlight the paradox between this structural diversity and the uniform anisotropic cell expansion taking place across all tissues during stem growth.
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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 | 0.001 | 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) | 0.000 | 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".