The decoration of specialized metabolites influences stylar development
Bibliographic record
Abstract
Plants produce many different specialized (secondary) metabolites that function in solving ecological challenges; few are known to function in growth or other primary processes. 17-Hydroxygeranylinalool diterpene glycosides (DTGs) are abundant herbivory-induced, structurally diverse and commonly malonylated defense metabolites in Nicotiana attenuata plants. By identifying and silencing a malonyltransferase, NaMaT1, involved in DTG malonylation, we found that DTG malonylation percentages are normally remarkably uniform, but when disrupted, result in DTG-dependent reduced floral style lengths, which in turn result from reduced stylar cell sizes, IAA contents, and YUC activity; phenotypes that could be restored by IAA supplementation or by silencing the DTG pathway. Moreover, the Nicotiana genus-specific JA-deficient short-style phenotype also results from alterations in DTG malonylation patterns. Decorations of plant specialized metabolites can be tuned to remarkably uniform levels, and this regulation plays a central but poorly understood role in controlling the development of specific plant parts, such as floral styles.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".