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Heterocyclic Amaryllidaceae Alkaloids: Biosynthesis and Pharmacological Applications

2016· review· en· W2514026372 on OpenAlexaff
Tarun Hotchandani, Isabel Desgagné‐Penix

Bibliographic record

VenueCurrent Topics in Medicinal Chemistry · 2016
Typereview
Languageen
FieldChemistry
TopicChemical synthesis and alkaloids
Canadian institutionsUniversité du Québec à Trois-Rivières
Fundersnot available
KeywordsAmaryllidaceae AlkaloidsAmaryllidaceaeBiosynthesisChemistryTraditional medicineBiologyBotanyBiochemistryMedicineGene

Abstract

fetched live from OpenAlex

Amaryllidaceae alkaloids (AAs), which are natural heterocyclic compounds, are isolated from Amaryllidaceae plants such as narcissus, snowdrop and spider lily. AAs have been extensively studied due to their multiple pharmacological properties. Nevertheless, knowledge of AA synthesis in plants is lacking and most genes encoding enzymes involved in their production remain unknown. AAs are structurally complex compounds which are challenging for total chemical synthesis that is economically viable. Therefore the understanding of AA biosynthesis could allow for the development of biotechnologies for the production of natural AAs or analogues, maintaining or improving their pharmacological properties. In this review, we describe the progress regarding the biosynthesis and pharmacological properties of AAs. The most recent developments in neurological, anti-cancer and anti-microbial bioactivities of heterocyclic AAs are covered.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.003

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 head0.047
GPT teacher head0.355
Teacher spread0.308 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations30
Published2016
Admission routes1
Has abstractyes

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