Adhesion and invasion of<i>Candida albicans</i>from periodontal pockets of patients with chronic periodontitis and diabetes to gingival human fibroblasts
Bibliographic record
Abstract
The objectives of this study were to evaluate clinical isolates of Candida albicans, particularly their adhesion to and invasion of gingival human fibroblasts in culture and to measure nitric oxide concentration (NO) produced by fibroblasts in the presence of these yeasts. Sixteen strains of C. albicans isolated from patients with chronic periodontitis and diabetes mellitus type II were divided on the basis of phenotypic tests into two groups, i.e., highly or weakly hydrophobic. Primary cultures of human fibroblasts were isolated from gingival biopsies and after subsequent subcultures, the cells were seeded into culture plates and incubated for 24 h. C. albicans strains were inoculated into these plates and maintained for 2 and 4 h to assess their adhesion and invasion, respectively. The number of adherent or invasive yeasts was evaluated by assessing colony-forming units (CFU). The production of NO by fibroblasts was also quantified. The results showed that strains with high hydrophobicity had a greater ability to adhere and invade fibroblasts (p < 0.05, ANOVA and Tukey). The production of NO was higher for the most hydrophobic strains, but did not reach statistical difference with the weakly hydrophobic isolates. These data indicated that the hydrophobicity may play a role in the adhesion and invasion of C. albicans in fibroblast cultures.
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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 | 0.000 | 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".