Changing spaces: the <i>Arabidopsis</i> mucilage secretory cells as a novel system to dissect cell wall production in differentiating cellsThis review is one of a selection of papers published in the Special Issue on Plant Cell Biology.
Bibliographic record
Abstract
As the outer boundary of plant cells, the cell wall is integral to all aspects of plant growth, development, and interactions with the environment. Dicot primary cell walls are composed of a network of cellulose, hemicellulose and proteins embedded in a matrix of acidic pectins. Pectins are synthesized in the Golgi apparatus by the sequential addition of nucleotide sugars by glycosyltransferases, following which they are secreted to the apoplast. During their differentiation, the mucilage secretory cells (MSCs) of the Arabidopsis seed coat undergo sequential biosynthesis and secretion of a primarily pectinaceous mucilage followed by secondary cell wall production. Several genes affecting MSC differentiation have been identified with roles ranging from the production of nucleotide sugar substrates for pectin synthesis to putative cell wall modification enzymes to transcription factors required to control MSC differentiation. These preliminary studies of the MSCs demonstrate that they will play a valuable role in gene discovery related to cell wall production and modification. Furthermore, they have the potential to become an important system in which to study the interaction and regulation of pectin biosynthetic factors in differentiating cells. These results will contribute to answering the important question of how cell wall production and modification occur throughout a growing plant living in a complex environment.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 teacher head, 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".