Morphological and histochemical characterization of the secretory sites of bioactive compounds in leaves of <i>Lantana camara</i> L. (Verbenaceae)
Bibliographic record
Abstract
Lantana camara L. is a species of Verbenaceae known for its aromatic and medicinal properties. Compounds extracted from its leaves are used to treat infections of the respiratory tract and have demonstrated antimicrobial potential and repellent action to Aedes mosquitoes. Our aim was to identify and characterize the main production sites of the biologically active substances in the leaf blades of L. camara. Leaf samples were collected from plants living in the Brazilian Cerrado and processed according to standard techniques in plant anatomy and histochemistry as well as scanning and transmission electron microscopy. Six morphotypes of glandular trichomes (I–VI) were identified; they differ in shape and size, number of constituent cells, subcellular aspects, and form of accumulation, as well as release and composition of the secretion. Idioblasts producing hydrophilic and lipophilic substances were observed in the mesophyll and may be associated with protection of the plant against herbivores and pathogens and maintenance of the water potential of leaf tissues, complementing the action of glandular trichomes. Our results contribute to the understanding and knowledge of the sites responsible for the production of substances with ecological and medicinal value in Verbenaceae species, and may provide a foundation for future studies in different areas of science focusing on the manipulation of this production.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".