<i>Trichophyton tonsurans</i> strains from Brazil: phenotypic heterogeneity, genetic homology, and detection of virulence genes
Bibliographic record
Abstract
The objective of this study was to establish the phenotypical and molecular patterns of clinical isolates of Trichophyton tonsurans circulating in the state of Ceará, northeastern Brazil. For this purpose, 25 T. tonsurans strains isolated from independent cases of tinea capitis in children were phenotypically evaluated regarding their macro- and micro-morphological characteristics, vitamin requirements, urease production, and antifungal susceptibility. The molecular characterization was carried out with random amplified polymorphic DNA molecular markers and M13 fingerprinting. The presence of the genes CarbM14, Sub2, CER, URE, ASP, PBL, and LAC, which encode enzymes related to fungal virulence, was also evaluated. Finally, melanin production was assessed through specific staining. The data obtained demonstrated that these T. tonsurans strains have considerable phenotypical variation, although they showed a low degree of genetic polymorphism according to the markers used. The genes CarbM14, Sub2, CER, and URE were detected in all the analyzed strains. The gene LAC was also identified in all the strains, and melanin synthesis was phenotypically confirmed. The strains were susceptible to antifungals, especially itraconazole (GM = 0.06 μg/mL) and ketoconazole (GM = 0.24 μg/mL). Therefore, T. tonsurans strains can present great phenotypical heterogeneity, even in genetically similar isolates. Moreover, the presence of the LAC gene indicates the possible participation of melanin in the pathogenesis of these dermatophytes.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".