Promoting Mineralization at Biological Interfaces with Novel Amelotin-based Bio-Nano Complexes
Bibliographic record
Abstract
According to the World Health Organization, dental caries is the most prevalent chronic disease worldwide. Remineralization of demineralized dentin, especially within the restorative material and tooth tissue interface, is of considerable interest in restorative dentistry since it may improve bond stability and prevent restorative failures.Amelotin (AMTN) is an enamel protein first identified in our lab. AMTN is expressed during the maturation stage of enamel formation and has been shown to promote mineral formation. In native tissue, AMTN is secreted into a microenvironment mostly made of nano-sized hydroxyapatite. Hydroxyapatite is the major inorganic component of the mineralized portion of the tooth. Furthermore, hydroxyapatite is one of the most biocompatible materials used in mineralized tissue regeneration. Therefore, this PhD project aimed to test the hypothesis that AMTN-coated hydroxyapatite nanoparticles (HANP) promote mineralization at collagenous interfaces. This PhD project comprises 3 phases: In phase I, a method for functionalizing HANP with AMTN/AMTN-Col was. HANP were synthesized and characterized. The nanoparticles were functionalized with AMTN or AMTN-Col. The successful coating of the nanoparticles with the proteins was confirmed using the immunogold-labelling technique. In phase II, 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. The extent of mineral formation on collagen gel and the remineralization of demineralized dentin were studied with scanning electron microscopy (SEM). Accelerated mineral formation in bio-nano complexes treated samples was observed in all model systems. In phase III, the clinical utilization of bio-nano complexes in bio-integration and enhancing the bond strength of a resin-based dental restoration were investigated. The bio-nano complexes were applied as a pretreatment on dentin prior to adhesive application. Shear bond strength values indicated that pretreatment of dentin with the bio-nano complexes significantly improved shear bond strength. Conclusion: We have shown that AMTN-based bio-nano complexes promote mineral formation on collagenous interfaces. Our findings can serve as the basis for the development of novel bioinspired nanomaterials to improve dental restoration longevity.
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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".