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Record W4395022334 · doi:10.1093/jxb/erae187

Navigating <i>Amaryllidaceae</i> alkaloids: bridging gaps and charting biosynthetic territories

2024· review· en· W4395022334 on OpenAlexafffund
Nuwan Sameera Liyanage, Fatima Awwad, Karen Cristine Gonçalves dos Santos, Thilina U. Jayawardena, Natacha Mérindol, Isabel Desgagné‐Penix

Bibliographic record

VenueJournal of Experimental Botany · 2024
Typereview
Languageen
FieldChemistry
TopicChemical synthesis and alkaloids
Canadian institutionsInnovation and Economic Development Trois RivièresUniversité du Québec à Trois-Rivières
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research Chairs
KeywordsAmaryllidaceae AlkaloidsBiosynthesisAmaryllidaceaeBiologyComputational biologyBiotechnologyBiochemistryBotanyGene

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.754
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.021
GPT teacher head0.324
Teacher spread0.303 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designOther design
Domainnot available
GenreReview

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".

Quick stats

Citations14
Published2024
Admission routes2
Has abstractyes

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