Terpenoid Biosynthesis and Specialized Vascular Cells of Conifer Defense
Bibliographic record
Abstract
Defense-related terpenoid biosynthesis in conifers is a dynamic process closely associated with specialized anatomical structures that allows conifers to cope with attack from many potential pests and pathogens. The constitutive and inducible terpenoid defense of conifers involves several hundred different monoterpenes, sesquiterpenes and diterpenes. Changing arrays of these many compounds are formed from the general isoprenoid pathway by activities of large gene families for two classes of enzymes, the terpene synthases and the cytochrome P450-dependent monooxygenases of the CYP720B group. Extensive studies have been conducted on the genomics, proteomics and molecular biochemical characterization of these enzymes. Many of the conifer terpene synthases are multi-product enzymes, and the P450 enzymes of the CYP720B group are promiscuous in catalyzing multiple oxidations, along homologous series of diterpenoids, from a broad spectrum of substrates. The terpene synthases and CYP720B genes respond to authentic or simulated insect attack with increased transcript levels, protein abundance and enzyme activity. The constitutive and induced oleoresin terpenoids for conifer defense accumulate in preformed cortical resin ducts and in xylem trauma-associated resin ducts. Formation of these resin ducts de novo in the cambium zone and developing xylem, following insect attack or treatment of trees with methyl jasmonate, is a unique feature of the induced defense of long-lived conifer trees.
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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 | 0.000 |
| 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".