Can Resin Monomers and By-Products Damage Collagen?
Bibliographic record
Abstract
Hybrid layers degrade due to endogenous collagenolytic enzymes and adhesive hydrolysis. Adhesive hydrolysis releases by-products that, along with uncured monomers, may have an adverse effect on collagen fibrils and contribute to the dissolution of the hybrid layer in resin-dentin bonds. The aim of this study was to investigate the effects of methacrylate monomers and corresponding by-products on collagen type I. Tendon fibers (TFs) from mouse tail were incubated with BisGMA 0.1%, BisEMA 0.1%, UDMA 0.1%, HEMA 0.1%, TEG-DMA 0.1%, methacrylic acid 0.025% (MAA), pyruvic acid 0.025% (PA), trypsin as positive control (PC), and water/ethanol as negative control for 1 h, 6 h, 24 h, 72 h, and 7 d. At each period, the specimens were tested mechanically (tensile strength and elastic modulus) and the storage medium tested for hydroxyproline (HPY) release and expressed as percentage of collagen solubilization (%CS). The TFs were morphologically analyzed by a Nikon-Eclipse 80i microscope. Incubation media and time affected TFs in different ways. The incubation of TFs with PA or MAA caused significant damage to the structure, reducing properties and increasing %CS to levels similar or higher than that of trypsin PC. Incubation in the monomers BisGMA 0.1%, BisEMA 0.1%, UDMA 0.1%, HEMA 0.1%, and TEG-DMA 0.1% did not cause hydroxyproline release, and their effects on the TF mechanical properties varied and were possibly related to dehydration. Methacrylate monomers and their by-products can adversely affect TF structure and properties. The findings indicate that collagen degradation in resin-dentin bonds can also be caused by by-products of the adhesive.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".