Interfacial Biomaterial–Dentin Bacterial Biofilm Proliferation and Viability Is Affected by the Material, Aging Media and Period
Bibliographic record
Abstract
Biomaterial−dentin interfaces undergo degradation over time, allowing salivary, tissue fluid, and bacterial movement between the root filling or restoration and dentin. This study aims to investigate the effect of aging in simulated human salivary/bacterial/blood esterases (SHSE) on proliferation and viability of Enterococcus faecalis biofilm within the dentin interface with four materials used to fill/restore the endodontic space. Root canals of human anterior teeth were prepared and filled with gutta-percha and one of the following: self-cured resin composite (BisfilTM 2B, Bisco, Schaumburg, IL, USA) with either self-etch (SE) (EasyBond) or total-etch (TE) (ScotchbondTM, 3M, Saint Paul, MN, USA) methacrylate-based adhesives, epoxy-resin sealer (AH Plus®, Dentsply Sirona, York, PA, USA), or bioceramic sealer (EndoSequence® BC Sealer™, Brasseler USA, Savannah, GA, USA). Specimens were aged in SHSE or phosphate-buffered saline (PBS) for up to 360 days, followed by cultivation of steady-state E. faecalis biofilm. Depth and viability of interfacial bacterial biofilm proliferation were assessed by confocal laser scanning microscopy and live/dead staining. Data were analyzed using three-way ANOVA and Scheffe’s post hoc analyses. Initial depths of biofilm proliferation were similar among material groups (p > 0.05). All groups showed significantly deeper biofilm proliferation with increased aging period (p < 0.05). SHSE aging increased interfacial biofilm depth for TE, SE and BC (p < 0.05) but not AH. For unaged interfaces, BC exhibited the lowest ratio of live bacteria, followed by AH, TE, and SE (p < 0.05). Interfacial bacterial biofilm proliferation and viability were dependent on the biomaterial, aging media, and period.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".