Navigating <i>Amaryllidaceae</i> alkaloids: bridging gaps and charting biosynthetic territories
Bibliographic record
Abstract
Amaryllidaceae alkaloid (AA) biosynthesis has garnered significant attention in recent years, particularly with the commercialization of galanthamine as a treatment for the symptoms of Alzheimer's disease. A significant amount of research work over the last eight decades has focused on the understanding of AA biosynthesis, starting from early radiolabelling studies to recent multi-omics analysis with modern biotechnological advancements. Those studies enabled the identification of hundreds of metabolites, the characterization of biochemical pathways, and an understanding of the environmental stimuli and of the molecular regulation of these pharmaceutically and agriculturally important metabolites. Despite numerous studies, there remain significant gaps in understanding the biosynthesis of AAs in Amaryllidaceae plants. As such, further research is needed to fully elucidate the metabolic pathways and facilitate their production. This review aims to provide a comprehensive summary of the current state of knowledge on AA biosynthesis, from elicitation of expression of transcription factors in the cell nucleus to alkaloid transport in the apoplast, and to highlight the challenges that need to be overcome for further advancement.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".