Phosphoric acid containing proanthocyanidin enhances bond stability of resin/dentin interface
Bibliographic record
Abstract
Proanthocyanidin (PA) is a promising dentin biomodifier due to its ability to stabilize collagen fibrils against degradation by matrix metalloproteinases (MMPs); however, the most effective protocol to incorporate PA into bonding procedures is still unclear. This study evaluated the effect of dentin biomodification with a PA acid etchant on MMP activity, adhesive interface morphology and resin-dentin microtensile bond strength. Sound extracted human molars were flattened to expose dentin and acid-etched for 15 s according to the groups: EXP - experimental phosphoric acid; EXP+PA - experimental phosphoric acid 10% PA; TE - total-etching system; SE - self-etching system. Samples were restored with composite resin and stored in distilled water (37ºC). MMP activity and interface morphology were analyzed after 24 h by in situ zymography (n=6) and scanning electron microscopy (n=3), respectively. The resin-dentin microtensile bond strength (μTBS) was evaluated after 24 h and 6 months storage (n=6). Significantly higher MMP activity was detected in etched dentin compared with untreated dentin (p<0.05), but no difference among acid groups was found. Resin tags and microtags, indicative of proper adhesive system penetration in dentinal tubules and microtubules, were observed along the hybrid layer in all groups. There was no difference in μTBS between 24 h and 6 months for EXP+PA; moreover, it showed higher long-term μTBS compared with TE and EXP (p<0.05). The results suggest that 15 s of biomodification was not sufficient to significantly reduce MMP activity; nonetheless, EXP+PA was still able to improve resin-dentin bond stability compared with total- and self-etching commercial systems.
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 | 0.000 |
| 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".