Quantification of Bacterial DNA from Infected Human Root Canals Using qPCR and DAPI after Disinfection with Established and Novel Irrigation Protocols
Bibliographic record
Abstract
The removal of bacterial infections within the root canal system is still a challenge. Therefore, the cleansing effect of established and new irrigation-protocols (IP) containing silver diamine fluoride (SDF) 3.8% on the whole root canal system was analyzed using quantitative PCR (qPCR) and 4′,6-diamidino-phenylindole-(DAPI)-staining. Extracted human premolars were instrumented up to F2 (ProTaper Gold) under NaCl 0.9% irrigation and incubated with Enterococcus faecalis for 42 days. Subsequently, different ultrasonically agitated IP were applied to the roots: control (no irrigation), 1. NaOCl 3%, EDTA 20%, CHX 2%, 2. NaOCl 3%, EDTA 20%, 3. NaOCl 3%, EDTA 20%, SDF 3.8%, 4. SDF 3.8%, and 5. NaCl 0.9%. One half of the root was investigated fluorescent-microscopically with DAPI. The other half was grinded in a cryogenic mill and the bacterial DNA was quantified with qPCR. The qPCR results showed a statistically significant reduction of bacteria after the application of IP 1, 2, and 3 compared to the control group. While IP 4 lead to a bacterial reduction which was not significant, IP 5 showed no reduction. These data corresponded with DAPI staining. With qPCR a new molecular-biological method for the investigation of the complete root canal system was implemented. The novel IP 3 had an equally good cleansing effect as the already established IP.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".