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In vitro susceptibility of the seven Malassezia species to ketoconazole, voriconazole, itraconazole and terbinafine

2000· article· en· W1829483440 on OpenAlexaff
Aditya K. Gupta, Yatika Kohli, A. Li, Jan Faergemann, Richard C. Summerbell

Bibliographic record

VenueBritish Journal of Dermatology · 2000
Typearticle
Languageen
FieldMedicine
TopicNail Diseases and Treatments
Canadian institutionsMinistry of Health and Long Term CareUniversity of TorontoSunnybrook Health Science Centre
Fundersnot available
KeywordsTerbinafineMalasseziaKetoconazoleVoriconazoleItraconazoleAzoleMicrobiologyBiologyMinimum inhibitory concentrationAntifungalAntimicrobial

Abstract

fetched live from OpenAlex

Fifty-five strains, either authentic or ex-type, of seven Malassezia species were investigated for in vitro susceptibility to various concentrations (0.03-64.0 microg/mL) of three azole drugs, ketoconazole, voriconazole and itraconazole, as well as the allylamine terbinafine, using the agar dilution method. All strains of the seven Malassezia species were susceptible to the three azole drugs at low concentrations. M. furfur, M. sympodialis, M. slooffiae, M. pachydermatis, M. globosa, M. obtusa and M. restricta were most sensitive to ketoconazole and itraconazole, with minimum inhibitory concentrations (MICs) ranging from < or = 0.03 to 0.125 microg/mL. The recently introduced antifungal, voriconazole, was also very effective, with MIC80 values < or = 0.03 microg/mL for 80% of strains. MICs of terbinafine against the seven Malassezia species ranged from </= 0.03 to 64.0 microg/mL. There were variations in susceptibility of the seven Malassezia species to ketoconazole, voriconazole, itraconazole and terbinafine. Strains of M. furfur, M. globosa and M. obtusa were more tolerant to terbinafine than the remaining Malassezia species; M. sympodialis was highly susceptible. M. furfur strains tested with terbinafine ranged from highly susceptible to relatively resistant. Correct identification of Malassezia species could facilitate selection of appropriate antifungal therapy.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.047
Threshold uncertainty score0.564

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0010.000

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 head0.242
Teacher spread0.236 · 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.

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

Citations146
Published2000
Admission routes1
Has abstractyes

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