Overcoming the challenges of preserving lipid‐rich<i>Cannabis sativa</i>L. glandular trichomes for transmission electron microscopy
Bibliographic record
Abstract
Cannabis glandular trichomes produce and store an abundance of lipidic specialised metabolites (e.g. cannabinoids and terpenes) that are consumed by humans for medicinal and recreational purposes. Due to a lack of genetic resources and inherent autofluorescence of cannabis glandular trichomes, our knowledge of cannabinoid trafficking and secretion is limited to transmission electron microscopy (TEM). Advances in cryofixation methods has resulted in ultrastructural observations closer to the 'natural state' of the living cell, and recent reports of cryofixed cannabis trichome ultrastructure challenge the long-standing model of cannabinoid trafficking proposed by ultrastructural reports using chemically fixed samples. Here, we compare the ultrastructural morphology of cannabis glandular trichomes preserved using conventional chemical fixation and ultrarapid cryofixation. We show that chemical fixation results in amorphous metabolite inclusions surrounding the organelles of glandular trichomes that were not present in cryofixed samples. Vacuolar morphology in cryofixed samples exhibited homogenous electron density, while chemically fixed samples contained a flocculent electron dense periphery and electron lucent lumen. In contrast to the apparent advantages of cryopreservation, fine details of cell wall fibre orientation could be observed in chemically fixed glandular trichomes that were not seen in cryofixed samples. Our data suggest that chemical fixation results in intracellular artefacts that impact the interpretation of lipid production and trafficking, while enabling greater detail of extracellular polysaccharide organisation.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".