A dysbiotic mycobiome dominated by <i>Candida albicans</i> is identified within oral squamous-cell carcinomas
Why this work is in the frame
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Bibliographic record
Abstract
The aim of this study was to characterize the mycobiome associated with oral squamous-cell carcinoma (OSCC). DNA was extracted from 52 tissue biopsies (cases: 25 OSCC; controls: 27 intra-oral fibro-epithelial polyps [FEP]) and sequenced for the fungal internal transcribed spacer 2 region using Illumina™ 2 x300bp chemistry. Merged reads were classified to species level using a BLASTN-algorithm with UNITE’s named species sequences as reference. Downstream analyses were performed using QIIME™ and linear discriminant analysis effect size. A total of 364 species representing 160 genera and two phyla (Ascomycota and Basidiomycota) were identified, with Candida and Malassezia making up 48% and 11% of the average mycobiome, respectively. However, only five species and four genera were detected in ≥50% of the samples. The species richness and diversity were significantly lower in OSCC. Genera Candida, Hannaella, and Gibberella were overrepresented in OSCC; Alternaria and Trametes were more abundant in FEP. Species-wise, Candida albicans, Candida etchellsii, and a Hannaella luteola–like species were enriched in OSCC, while a Hanseniaspora uvarum–like species, Malassezia restricta, and Aspergillus tamarii were the most significantly abundant in FEP. In conclusion, a dysbiotic mycobiome dominated by C. albicans was found in association with OSCC, a finding worth further investigation.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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 it