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Effect of Simulated Dental Pulpal Pressure Using Fetal Bovine Serum for the Bonding Performance of Contemporary Adhesive to Dentin.

Yitong LiMasahiko MaenoCarolina Cecilia Cifuentes-JimenezMei KomotoYunqing LiuYoichiro NaraHidehiko SanoPedro Alvarez-LloretMônica YamautiAtsushi Tomokiyo
Published in: Polymers (2024)
This study evaluated the effect of simulated pulpal pressure (SPP) conditions and storage time on contemporary adhesive systems' microtensile bond strength (µTBS) to dentin. Extracted human molars were prepared and randomly divided into four groups according to the adhesives: Clearfil Megabond 2 (CSE), Beautibond Xtreme Universal (BXU), G2-Bond (G2B), and Scotchbond Universal Plus (SBP). Each adhesive group was further divided following the SPP conditions: control with no simulation (SPP-CTR), SPP with distilled water (SPP-DTW), and SPP with fetal bovine serum (SPP-FBS). Resin composite build-ups were prepared, and teeth were stored in water (37 °C) for 24 h (24 h) and 3 months (3 m). Then, teeth were sectioned to obtain resin-dentin bonded beams and tested to determine the µTBS. Data were analyzed using three-way ANOVA, Tukey post hoc tests (=0.05), and Weibull failure analysis. Failure mode was observed using scanning electron microscopy. The µTBS response was affected by adhesive systems, simulated pulpal pressure conditions, and storage time. SPP-CTR groups presented a higher overall bond strength than SPP-DTW and SPP-FBS, which were not significantly different from each other. Only for SBP, the SPP-FBS group showed higher µTBS than the SPP-DTW group. The Weibull analysis showed that the bonding reliability and durability under SPP-DTW and SPP-FBS were inferior to SPP-CTR, and the 24 h bonding quality of adhesives to dentin was superior to that of 3 m. SPP drastically reduced the µTBS of all adhesives to dentin regardless of solution (distilled water or fetal bovine serum). Storage after 3 m also decreased µTBS despite the SPP condition.
Keyphrases
  • machine learning
  • endothelial cells
  • electron microscopy
  • big data
  • oral health