Development of Functional and Hydrolytically Stable Vinyl Monomers as Methacrylate Dental Resin Restorative Alternatives
Bibliographic record
Abstract
Dental resin-based restorative (RBR) materials represent the most ubiquitous biomaterials utilized globally. Methacrylate (MA)-ester based monomers - present in RBRs since the 1960s - experience significantly elevated rates of failure compared to previously used silver/amalgam fillings attributed to their hydrolysis reported in both simulated and in vivo environments. There is currently no alternative RBR chemistry that matches the functional and clinical workflow considerations of MA-RBRs while addressing their limited-service lives. The objective of this work is to utilize a systematic framework to develop alternative hydrolytically-stable monomers (HSMs), assessing key physical properties, biostability, and cytocompatibility towards eliminating or reducing the biodegradation of RBRs. This process yielded HSMs (referreed to as 3BE, 3TE) that matched the physical properties of MA-control materials, including viscosity, polymerization conversion, hydrophilicity, water uptake, and surface hardness (p > 0.05), while outperforming MA-based materials in all simulated oral environments, showing improved biostability in reconstituted human saliva, simulated human salivary esterase (SHSE), bacterial culture, and acidic media (p < 0.05). Additionally, HSMs were found to be less cytotoxic than commercial MA-monomers (p < 0.05) and unlikely to be genotoxic. Therefore, the HSMs and associated resins developed in this study have the potential to significantly improve the clinical service life of RBRs, without compromising their fundamental features.
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 | 0.001 |
| 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".