Longitudinal bond strength of a universal adhesive and chemical dentin characterization under different acid etching protocols
Bibliographic record
Abstract
OBJECTIVE: This study aimed to analyze the longitudinal bond strength of a universal adhesive and chemically characterize the dentin substrate under different acid etching protocols. METHODOLOGY: Dentin samples were etched with polyacrylic acid 25% (PAA) for 10 seconds (n=3) and phosphoric acid 32% (PA) for 15 seconds (n=3) and analyzed by Fourier transform infrared spectroscopy - attenuated total reflectance (FTIR-ATR) before and after treatment. For collagen degradation, samples (n=12) were divided into 3 groups: PAA, PA, and Deionized water (control), and analyzed by the quantity of solubilized type I collagen C-terminal cross-linked telopeptides and solubilized C-terminal peptide in relation to total protein concentration (ICTPtp and CTXtp) and by their ultimate tensile strength (UTS). For the adhesive interface analysis, dentin samples (n=72) were divided into 3 groups: PAA, PA, and Self-etch (SE), and subdivided into 2 groups: 24 h (baseline) and 1 year. The following tests were performed: microtensile bond strength (μTBS) (n=48), scanning electron microscopy (SEM) (n=12), and nanoleakage (n=12). RESULTS: The FTIR of PAA showed lower reduction of the peaks in the phosphate group when compared to PA. For ICTPtp, PA showed a significantly higher value. For CTXtp, PA and PAA groups failed to statically differ from each other. UTS was significantly lower for PA. For μTBS, storage time significantly affected bond strength. The results were unaffected by the etching protocol. For SEM, after 1 year, PA had little evidence of degradation in the upper third of the adhesive interface in comparison to the other groups. Nanoleakage showed no considerable silver impregnation after 1 year in the SE group. CONCLUSION: The use of PAA prior to a universal adhesive (when compared to PA) represents a less aggressive type of etching to dentin. However, self-etching still seems to be the best option for universal adhesive systems that have functional monomers in their composition.
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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) | 0.000 | 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) | 0.002 | 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".