Synthesis and challenges of fluorinated divinyl urethane monomers as a strategy for masking hydrolytic sensitive methacrylate groups in resin composites
Bibliographic record
Abstract
OBJECTIVE: The biodegradation of methacrylate (MA)-based dental restoratives has been suggested to contribute to a loss of adhesion and subsequent detachment, or secondary caries, both major causes of restoration failure. Previous studies have demonstrated that intermolecular interactions between resin monomers may affect the hydrolytic-susceptibility of composites. Altering the intermolecular interactions by shielding or masking the hydrolytically-susceptible ester groups found in MA monomers could be an effective strategy to mitigate the biodegradation of resin composites. The objective of this work was to assess whether shielding/masking MAs using fluorinated groups could improve the biostability of experimental composites. METHODS: H NMR), and formulated into experimental resin composites (FC, 65 wt%, microfill). FCs were assessed for interactions with water (water contact angle, water sorption, gel fraction), mechanical properties (both compressive and flexural strength and modulus), cytocompatibility, resistance to biodegradation using simulated human salivary esterase (SHSE) and compared to a control composite (CC) without FM. RESULTS: Integration of FMs was found to generally decrease both the physical and mechanical properties under all incubation conditions when compared to the CC. Additionally, all FCs had a negative influence on composite biodegradation following immersion in SHSE when compared to the CC. SIGNIFICANCE: Shielding/masking MA-esters inherently inserts molecular spaces between the polymer chains within the resin network, and shielding is likely not possible while also maintaining the necessary cohesive forces that regulate the physical and mechanical properties of resin composites. Novel dental resin development should seek to remove/replace vulnerable ester-containing MAs rather that adopting a shielding/masking approach.
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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) | 0.001 | 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 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".