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Record W4413797337 · doi:10.3762/bjoc.21.135

Convenient alternative synthesis of the <i>Malassezia</i> -derived virulence factor malassezione and related compounds

2025· letter· en· W4413797337 on OpenAlexafffund
Karu Ramesh, Stephen L. Bearne

Bibliographic record

VenueBeilstein Journal of Organic Chemistry · 2025
Typeletter
Languageen
FieldMedicine
TopicNail Diseases and Treatments
Canadian institutionsDalhousie University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsChemistryYield (engineering)Virulence factorAcetic acidIndole testAspergillus fumigatusVirulenceCarbodiimideOrganic chemistryStereochemistryCombinatorial chemistryMicrobiologyBiochemistryBiology

Abstract

fetched live from OpenAlex

Lipophilic yeasts of the genus Malassezia are commensal fungi that constitute the normal skin microbiota but may become pathogenic. These fungi, especially M. furfur , convert tryptophan into various alkaloid indoles such as malassezione, which may serve as virulence factors. To facilitate testing of malassezione as an aryl hydrocarbon receptor agonist and potential glucokinase activator, we developed a convenient synthetic route from commercially available indole-3-acetic acid. Treatment of the N -Boc-protected indole-3-acetic acid with N -ethyl- N ′-(3-dimethylaminopropyl)carbodiimide (EDC) in the presence of DMAP generates the N , N ′-Boc-protected malassezione, which upon deprotection yields malassezione in an overall yield of ca. 20%. This is an improvement over the preparation of the isonitrile followed by an Fe hydride initiated isonitrile–olefin intramolecular coupling reaction, which generated malassezione with an overall yield of ca. 5%. Furthermore, the present method may also be used to prepare related compounds.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.004

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 head0.225
Teacher spread0.218 · 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 designBench or experimental
Domainnot available
GenreEmpirical

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

Citations0
Published2025
Admission routes2
Has abstractyes

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