Effects of co-overexpression of <i>ALDH1, CYP71AV1</i>, and <i>iaaM</i> on the density, length, and width of glandular secretory trichomes and the contents of artemisinin in <i>Artemisia annua</i>
Bibliographic record
Abstract
Sesquiterpene lactone artemisinin is one of the main agents used to treat malaria. Artemisinin is produced in the glandular secretory trichomes (GSTs) of Artemisia annua. The plant hormones and metabolic pathways regulate the artemisinin content of A. annua. It was possible to examine the functions of auxin, an important plant hormone, in the development of GSTs in A. annua by enhancing the expression of iaaM, which encodes a tryptophan monooxygenase involved in the biosynthesis of auxin. Additionally, the effects of co-overexpression of aldehyde dehydrogenase 1 ( ALDH1), P450 monooxygenase ( CYP71AV1), and iaaM on the density, length, and width of GSTs and the contents of artemisinin were further investigated. Results indicated that overexpression of iaaM might increase the density, length, and width of GSTs by enhancing auxin biosynthesis. This study also proved the key regulatory role of ALDH1 in the biosynthesis of artemisinin. Moreover, co-overexpression of ALDH1, CYP71AV1, and iaaM successfully increased the density, length, and width of GSTs and improved the artemisinin content in A. annua. Therefore, we established a theoretical basis for modifying artemisinin accumulation in this study by regulating the expression of auxin and artemisinin synthesis-related genes using a metabolic engineering method.
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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 | 0.001 |
| 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".