Effects of Etch-and-Rinse and Self-etch Adhesives on Dentin MMP-2 and MMP-9
Bibliographic record
Abstract
Auto-degradation of collagen matrices occurs within hybrid layers created by contemporary dentin bonding systems, by the slow action of host-derived matrix metalloproteinases (MMPs). This study tested the null hypothesis that there are no differences in the activities of MMP-2 and -9 after treatment with different etch-and-rinse or self-etch adhesives. Tested adhesives were: Adper Scotchbond 1XT (3M ESPE), PQ1 (Ultradent), Peak LC (Ultradent), Optibond Solo Plus (Kerr), Prime&Bond NT (Dentsply) (all 2-step etch-and-rinse adhesives), and Adper Easy Bond (3M ESPE), Tri-S (Kuraray), and Xeno-V (Dentsply) (1-step self-etch adhesives). MMP-2 and -9 activities were quantified in adhesive-treated dentin powder by means of an activity assay and gelatin zymography. MMP-2 and MMP-9 activities were found after treatment with all of the simplified etch-and-rinse and self-etch adhesives; however, the activation was adhesive-dependent. It is concluded that all two-step etch-and-rinse and the one-step self-etch adhesives tested can activate endogenous MMP-2 and MMP-9 in human dentin. These results support the role of endogenous MMPs in the degradation of hybrid layers created by these adhesives.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 |
| 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".