Periodontopathic bacterial adhesion to different restorative materials used to elevate proximal subgingival margins.
Hoda Saleh IsmailParveez Ahamed Abdul AzeesHanzhou WangAshraf Ibrahim AliRabab Elsayed Elaraby MehesenSalah Hasab MahmoudXiao-Dong ChenChih-Ko YehFranklin García-GodoyPublished in: European journal of oral sciences (2022)
This study compared the periodontopathic bacterial adhesion to four restorative materials used for deep margin elevation at 2, 24, and 48-h after incubation. Discs were produced from four restorative materials: resin modified glass ionomer, glass hybrid, flowable bulk fill resin composite, and bioactive ionic resin. Root dentin was used as control. Specimens were coated with saliva and used to culture a biofilm comprised of three strains of periodontopathic bacteria; Porphyromonas gingivalis, Prevotella intermedia, and Aggregatibacter actinomycetemcomitans. Bacterial adherence was assessed by colony count assay, crystal violet staining, and visualized using confocal laser scanning microscopy. Data were analyzed by two-way ANOVA followed by Tukey's post hoc tests. The adhesion values for the control specimens were significantly higher than for other materials, while those for the flowable bulk fill were significantly lower than for any other material within all evaluation assays. The 2-h incubation period showed the lowest adhesion values regardless of the group. The 48-h adhesion values were higher than the 24-h results in all groups except the flowable bulk fill. Microscopic imaging partially supported the findings of the measurements. In terms of periodontopathic bacterial adhesion, the tested flowable bulk fill may be preferable for subgingival use over other tested materials.
Keyphrases
- biofilm formation
- high resolution
- high throughput
- pseudomonas aeruginosa
- cell migration
- staphylococcus aureus
- escherichia coli
- candida albicans
- high speed
- cell adhesion
- type diabetes
- skeletal muscle
- peripheral blood
- metabolic syndrome
- mass spectrometry
- insulin resistance
- single molecule
- big data
- artificial intelligence
- photodynamic therapy
- solid state
- deep learning
- raman spectroscopy
- fine needle aspiration
- clinical evaluation