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 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 | 0.000 | 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".