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Record W1978732222 · doi:10.1039/b604400j

Metabolism of crucifer phytoalexins in Sclerotinia sclerotiorum: detoxification of strongly antifungal compounds involves glucosylation

2006· article· en· W1978732222 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueOrganic & Biomolecular Chemistry · 2006
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenomics, phytochemicals, and oxidative stress
Canadian institutionsUniversity of Saskatchewan
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSclerotinia sclerotiorumPhytoalexinChemistryAntifungalCruciferBiochemistryMicrobiologyBotanyBiologyResveratrol

Abstract

fetched live from OpenAlex

The strongly antifungal phytoalexins brassilexin and sinalexin were metabolized by the stem rot fungus Sclerotinia sclerotiorum to glucosyl derivatives, whereas the phytoalexins brassicanal A, spirobrassinin and 1-methoxyspirobrassinin, displaying lower antifungal activity, were transformed via non-glucosylating pathways. Significantly, these transformations led to metabolites displaying no detectable antifungal activity. The chemical characterization of all new metabolites as well as the chemistry of these processes and a facile chemical synthesis of 1-beta-D-glucopyranosylbrassilexin are reported. Overall, our results indicate that phytoalexins, strongly antifungal against S. sclerotiorum, are detoxified via glucosylation, which in turn suggests that S. sclerotiorum has acquired efficient glucosyltransferase(s) that can disarm some of the most active plant chemical defenses. Consequently, we suggest that these glucosylation reactions are potential metabolic targets to control S. sclerotiorum.

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.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.039
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.007
GPT teacher head0.213
Teacher spread0.206 · 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