Quantitative variation of biofilms among strains in natural populations of Candida albicans
Bibliographic record
Abstract
This study examined the quantitative variation of biofilm formation and its relationship to multilocus genotypes in 115 strains of the human pathogenic fungus Candida albicans. These strains were isolated from three sources: 47 from oral cavities of healthy volunteers, 31 from the environment and 37 from the vaginas of patients with candidiasis. For each strain, biofilm formation was quantified as the ability to adhere to and grow on polystyrene plastic surfaces. Confocal laser scanning microscopy was used to visualize and confirm biofilm formation. Two methods were used to quantify biofilm formation abilities: (i). the XTT reduction assay, and (ii). absorbance following staining by crystal violet dye. Results obtained by the two methods were significantly correlated. Furthermore, biofilm formation ability was positively correlated with cell surface hydrophobicity. The analyses indicated that strains from each of the three sources varied widely in biofilm formation abilities. However, little correlation was observed between biofilm formation and multilocus genotypes as determined by PCR-RFLP at 16 polymorphic loci, regardless of source of strain. Strains with the same or similar multilocus genotypes often showed very different biofilm formation abilities. The results demonstrated that natural clones and clonal lineages of C. albicans exhibited extensive quantitative variation in biofilm formation.
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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 | 0.001 | 0.003 |
| 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) | 0.000 | 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".