Cannabis glandular trichomes alter morphology and metabolite content during flower maturation
Bibliographic record
Abstract
The cannabis leaf is iconic, but it is the flowers of cannabis that are consumed for the psychoactive and medicinal effects of their specialized metabolites. Cannabinoid metabolites, together with terpenes, are produced in glandular trichomes. Superficially, stalked and sessile trichomes in cannabis only differ in size and whether they have a stalk. The objectives of this study were: to define each trichome type using patterns of autofluorescence and secretory cell numbers, to test the hypothesis that stalked trichomes develop from sessile-like precursors, and to test whether metabolic specialization occurs in cannabis glandular trichomes. A two-photon microscopy technique using glandular trichome intrinsic autofluorescence was developed which demonstrated that stalked glandular trichomes possessed blue autofluorescence correlated with high cannabinoid levels. These stalked trichomes had 12-16 secretory disc cells and strongly monoterpene-dominant terpene profiles. In contrast, sessile trichomes on mature flowers and vegetative leaves possessed red-shifted autofluorescence, eight secretory disc cells and less monoterpene-dominant terpene profiles. Moreover, intrinsic autofluorescence patterns and disc cell numbers supported a developmental model where stalked trichomes develop from apparently sessile trichomes. Transcriptomes of isolated floral trichomes revealed strong expression of cannabinoid and terpene biosynthetic genes, as well as uncharacterized genes highly co-expressed with CBDA synthase. Identification and characterization of two previously unknown and highly expressed monoterpene synthases highlighted the metabolic specialization of stalked trichomes for monoterpene production. These unique properties and highly expressed genes of cannabis trichomes determine the medicinal, psychoactive and sensory properties of cannabis products.
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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".