Gingival Microleakage of Class V Composite Restorations with Fiber Inserts
Bibliographic record
Abstract
AIM: This study investigated the effect of different fiber inserts (glass and polyethylene), bonding agents, and resin composites on the gingival margin microleakage of class V composite restorations. MATERIALS AND METHODS: Sixty premolars were sterilized and mounted in acrylic resin bases. Class V cavities were prepared buccally and lingually, 1 mm below the cementoenamel junction, comprising 12 groups (n = 10). In the experimental groups fiber inserts were cut and placed at the gingival seat, while the control groups had no inserts. Combinations of two composite materials, Filtek-Z250 and Filtek-LS (3M-ESPE), and four bonding agents, Clearfil SE bond (Kuraray) (C), Scotch Bond Multipurpose (3M-ESPE) (SB), Prime and Bond NT (Dentsply) (PB), and Filtek-LS (3M-ESPE) (LS) were used. Restorations were incrementally inserted and polymerized for 40s. Specimens were then stored in distilled water for 7 days and thermocycled for 500 cycles. Teeth surfaces were sealed with nail polish except for 1 mm around restoration margins and immersed in 2% red procion dye. Teeth were then sectioned buccolingually and dye penetration was assessed with five-point scale. Data were statistically-analyzed by Kruskal-Wallis, ANOVA and Tukey's tests (α = 5%). RESULTS: Mean microleakage scores varied from 0.40 (Groups C, C with polyethylene, LS, LS with polyethylene) to 1.50 (SB). CONCLUSION: Different bonding agents led to differences in microleakage scores where C and LS showed significantly lower microleakage than PB. SB had highest mean microleakage score, however, incorporation of fibers resulted in significant reduction in microleakage. CLINICAL SIGNIFICANCE: Class V resin composite restorations bonded with a total-etch adhesive had a significant reduction in mean microleakage scores when glass or polyethylene fibers were placed at the gingival cavo-surface margin. In contrast, for two self-etch adhesive systems, the incorporation of fibers had no significant effect on mean microleakage scores.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".