Vinca drug components accumulate exclusively in leaf exudates of Madagascar periwinkle
Bibliographic record
Abstract
The monoterpenoid indole alkaloids (MIAs) of Madagascar periwinkle (Catharanthus roseus) continue to be the most important source of natural drugs in chemotherapy treatments for a range of human cancers. These anticancer drugs are derived from the coupling of catharanthine and vindoline to yield powerful dimeric MIAs that prevent cell division. However the precise mechanisms for their assembly within plants remain obscure. Here we report that the complex development-, environment-, organ-, and cell-specific controls involved in expression of MIA pathways are coupled to secretory mechanisms that keep catharanthine and vindoline separated from each other in living plants. Although the entire production of catharanthine and vindoline occurs in young developing leaves, catharanthine accumulates in leaf wax exudates of leaves, whereas vindoline is found within leaf cells. The spatial separation of these two MIAs provides a biological explanation for the low levels of dimeric anticancer drugs found in the plant that result in their high cost of commercial production. The ability of catharanthine to inhibit the growth of fungal zoospores at physiological concentrations found on the leaf surface of Catharanthus leaves, as well as its insect toxicity, provide an additional biological role for its secretion. We anticipate that this discovery will trigger a broad search for plants that secrete alkaloids, the biological mechanisms involved in their secretion to the plant surface, and the ecological roles played by them.
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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 | 0.000 | 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 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".