Single cell mass spectrometry reveals intercellular compartmentalization of camptothecin biosynthesis in the tree <i>Camptotheca acuminata</i>
Bibliographic record
Abstract
Abstract The medicinal tree Camptotheca acuminata produces camptothecin, a monoterpenoid indole al- kaloid (MIA) precursor for several leading chemotherapeutic agents (Lorence and Nessler 2004). Alt- hough the biosynthesis of camptothecin remains poorly understood, a putative route has been hypothe- sized based on in planta metabolite profiling and feeding studies (Fig. 1a) (Sheriha and Rapoport 1976; Sadre et al. 2016). However, pathways proposed on whole-tissue or organ-level metabolomic and tran- scriptomic data lack resolution on the intricate, cell-specific compartmentalization of natural products biosynthesis. Such gaps could be addressed by single cell technologies, which have recently shown tremendous potential to transform gene discovery in herbaceous plants (Li et al. 2023; Zhan et al. 2023; Vu et al. 2024; Wu et al. 2024; McClune et al. 2025). Nevertheless, single cell mass spectrometry (scMS) has not been adapted for woody species, largely due to the challenges associated with their highly lignified tissue and complex cellular architecture. In this study, we developed an scMS pipeline for the woody tree C. acuminata to investigate the intercellular organization of camptothecin biosynthesis.
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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) | 0.001 | 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".