Comparison of Shear Bond Strength of Orthodontic Metal Brackets Adhered to Composite Restorations Pretreated with Er;Cr:YSGG and CO2 Lasers and Phosphoric Acid
Bibliographic record
Abstract
Background & Aim. The aim of this study was to compare the bond strength of the orthodontic brackets bonded to the composite restorations following preparations by CO2 and Er;Cr:YSGG lasers and conventional phosphoric acid etching adult orthodontic treatment. Materials & Methods. Class V cavities were prepared on the buccal surfaces of 60 acrylic teeth and restored by composite after etching by 37% acid-etch gel. The specimens’ surfaces were prepared randomly by 37% phosphoric acid etching or Er;Cr:YSGG or CO2 lasers. Central metal brackets were installed on the teeth's surfaces. The shear bond strength of the brackets to composite surfaces was measured by the crosshead speed of 1mm/min. The scores of the remaining adhesive on the surfaces were calculated by ARI index in 5 scales. The shear bond strength values and the ARI scores were analyzed by one-way ANOVA and Chi-square tests respectively. Results. There were no significant differences among the surface preparation methods regarding bond strength between composite surfaces and the brackets. Most specimens showed ARI index of 3 in the acid phosphoric etching. In CO2 laser application, ARI index of 2 and 3 were more frequent. In Er;Cr:YSGG laser, ARI index of 3 was predominant. No significant differences existed among 3 modalities regarding scores of ARI index. Conclusion. Irradiation of CO2 and Er;Cr:YSGG lasers is recommended for clinical applications due to adequate bond strength created between the brackets and composite surfaces as well as advantages such as lower chair time and no damage to the gingival tissues.
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 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 | 0.000 |
| 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".