Promoting mineralization at biological interfaces Ex vivo with novel amelotin-based bio-nano complexes
Bibliographic record
Abstract
Interfacial failure at the resin-dentin interface is a significant disadvantage of resin-based dental restoration. In this study, we created bio-inspired bio-nano complexes using the enamel protein amelotin (AMTN) or AMTN with an engineered collagen-binding site (AMTN-Col) to coat hydroxyapatite nanoparticles (HANP). The resulting nano-bio complexes, AMTN-HANP and AMTN-Col–HANP, were evaluated for their ability to promote collagen mineralization. Our study comprises three separate phases. In phase I, developing a method for functionalizing HANP with AMTN/AMTN-Col was explored. HANP were synthesized and characterized using TEM, SAED-TEM, XRD and ATR-FTIR. The nanoparticles were functionalized with AMTN or AMTN-Col. The successful coating of the nanoparticles with the proteins was confirmed using a TEM image of immunogold-labelled samples. In phase II of the study, the mineralization potential of the synthesized bio-nano complexes was studied using model systems consisting of simulated body fluid (SBF), polymerized collagen gels, and dentin disks prepared from human extracted molars. Mineral formation in SBF was recorded with a light scattering assay using a microplate reader on 8 replicates of each sample per study time point. Statistical analysis was performed using one-way ANOVA and the Tukey test. Significance was assigned at P < 0.01. The extent of mineral formation on collagen gel and remineralization of demineralized dentin was studied with SEM. Accelerated mineral formation collagen mineralization of bio-nano complexes treated samples were observed in all model systems. In phase III of the study, the clinical utilization of AMTN/AMTN-Col coated HANP in bio-integration and enhancing the bond strength of a resin-based dental restoration and the dentin interface was investigated. The bio-nano complexes were applied as a pretreatment on dentin disks prepared from human extracted molars prior to the composite resin restoration. The micro-shear bond strength test was done on 8 samples per treatment group (a total of 32 samples). Statistical analysis on shear bond strength was performed using one-way ANOVA and the Tukey test. Significance was assigned at P < 0.01. Shear bond strength values indicated that pretreatment of dentin with the bio-nano complexes before adhesive application significantly improved shear bond strength. We have shown that AMTN based bio-nano complexes promote mineral formation on collagenous interfaces. Our findings can be the basis of new bio-inspired, bio-nano materials that may improve dental restoration longevity by enhancing the stability and integrity of the dentin-composite resin interface.
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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) | 0.000 | 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".