Antibacterial and smear layer removal ability of a novel irrigant, QMiX
Bibliographic record
Abstract
AIM: To assess in a laboratory experimental model the efficacy of a novel root canal irrigant, QMiX, against Enterococcus faecalis and mixed plaque bacteria in planktonic phase and biofilms. In addition, its ability to remove smear layer was examined. METHODOLOGY: Enterococcus faecalis and mixed plaque bacteria were exposed to QMiX, 2% chlorhexidine (CHX), MTAD and 1% sodium hypochlorite (NaOCl) for 5 s, 30 s and 3 min. Following exposure, samples were taken, serially diluted and grown aerobically and anaerobically on tryptic soy agar (TSA) plates or on blood agar plates for 24 and 72 h, respectively, to measure killing of bacteria. E. faecalis and plaque biofilms were grown for 3 weeks on collagen-coated hydroxyapatite or dentine discs and exposed for 1 and 3 min to QMiX, 2% CHX, MTAD, 1% and 2% NaOCl. The amount of killed bacteria in biofilms was analysed by confocal laser scanning microscopy using viability staining. Dentine blocks were exposed to QMiX and 17% EDTA for 5 min. The effectiveness of smear layer removal by the solution was evaluated using scanning electron microscopy. For statistical analysis, one-way analysis of variance and comparison of two proportions were used. RESULTS: QMiX and 1% NaOCl killed all planktonic E. faecalis and plaque bacteria in 5 s, while 2% CHX and MTAD were unable to kill all plaque bacteria in 30 s, and some E. faecalis cells survived even 3 min of exposure. QMiX and 2% NaOCl killed up to 12 times more biofilm bacteria than 1% NaOCl (P < 0.01), 2% CHX (P < 0.05; P < 0.001) and MTAD (P < 0.05; P < 0.001). QMiX removed smear layer equally well as EDTA (P = 0.18 × 10(-5)). CONCLUSION: QMiX and NaOCl were superior to CHX and MTAD under laboratory conditions in killing E. faecalis and plaque bacteria in planktonic and biofilm culture. Ability to remove smear layer by QMiX was comparable to EDTA.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".