Microbial adhesion and biofilm formation by Candida albicans on 3D-printed denture base resins
Bibliographic record
Abstract
This study evaluated surface properties and adhesion/biofilm formation by Candida albicans on 3D printed denture base resins used in 3D printing. Disc-shaped specimens (15 mm x 3 mm) of two 3D-printed resins (NextDent Denture 3D+, NE, n = 64; and Cosmos Denture, CO, n = 64) and a heat-polymerized resin (Lucitone 550, LU, control, n = 64) were analyzed for surface roughness (Ra μm) and surface free energy (erg cm-2). Microbiologic assays (90-min adhesion and 48-h biofilm formation by C. albicans) were performed five times in triplicate, with the evaluation of the specimens' surface for: (i) colony forming units count (CFU/mL), (ii) cellular metabolism (XTT assay), and (iii) fluorescence and thickness of biofilm layers (confocal laser scanning microscopy). Data were analyzed using parametric and nonparametric tests (α = 0.05). LU presented higher surface roughness Ra (0.329±0.076 μm) than NE (0.295±0.056 μm) (p = 0.024), but both were similar to CO (0.315±0.058 μm) (p = 1.000 and p = 0.129, respectively). LU showed lower surface free energy (47.47±2.01 erg cm-2) than CO (49.61±1.88 erg cm-2) and NE (49.23±2.16 erg cm-2) (p<0.001 for both). The CO and NE resins showed greater cellular metabolism (p<0.001) and CO only, showed greater colonization (p = 0.015) by C. albicans than LU in the 90-min and 48-hour periods. It can be concluded that both 3D-printed denture base resins are more prone to colonization by C. albicans, and that their surface free energy may be more likely associated with that colonization than their surface roughness.
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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".