The effect of histatin 5, adsorbed on PMMA and hydroxyapatite, on <i>Candida albicans</i> colonization
Bibliographic record
Abstract
The limited number of treatments for oral candidiasis resulted in the emergence of azole-resistant Candida albicans strains, thus enforcing the need for novel antifungal treatments. Although histatin 5 (H5) demonstrates antifungal activity, its inhibitory effect when adhered to hydroxyapatite and Polymetylmethacrylate (PMMA) surfaces, resembling conditions of the in vivo pellicle, remains unexplored. The objective of this in vitro study was to determine whether surface-adhered H5 inhibits the colonization of C. albicans on hydroxyapatite and/or PMMA. The C. albicans assay involved developing a mono-protein pellicle (either H5 or albumin) on hydroxyapatite and PMMA discs, introducing C. albicans and counting the number of adhered cells, throughout time, using scanning electron microscopy. A negative binomial statistical model and the Tukey-Kramer test were used for statistical analysis, with p < 0.01 indicating significance. H5-coated PMMA had significantly reduced number of cells compared to albumin-coated PMMA at 30, 90 and 1440 min (p < 0.0001), with the number of cells decreasing significantly in 90 and 1440 min (p < 0.0001). Similarly, H5-coated hydroxyapatite had significantly fewer cells compared to the albumin-coated surface at 90 and 1440 min (p < 0.0001), with the number of cells decreasing significantly at 30, 90 and 1440 min (p < 0.0001). In conclusion, C. albicans colonization was most inhibited by PMMA and hydroxyapatite-adhered H5 after 1440 min, illustrating the time-dependent effect of H5. In addition, yeast cells colonized albumin-coated PMMA, while dense hyphal networks formed on albumin-coated hydroxyapatite, suggesting that C. albicans morphology is influenced by the surface available for albumin adhesion.
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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 | 0.000 |
| 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".