Bacterial Culture and DNA Checkerboard for the Detection of Internal Contamination in Dental Implants
Bibliographic record
Abstract
PURPOSE: The aim of this in vitro study was to evaluate the bacterial leakage along the implant-abutment interface by the conventional bacterial culture and DNA Checkerboard hybridization method. MATERIALS AND METHODS: Twenty Branemark-compatible implants with a 3.75-mm diameter and external hexagonal platform were randomly placed in two groups of ten implant-abutment assemblies each. One group was used to analyze bacterial counts by DNA Checkerboard hybridization and the other by a conventional bacterial culture. Suspensions of Fusobacterium nucleatum (3 microl) were injected into the grooved internal cylinders of each implant assembly, and the abutment was connected by a 32 Ncm torque. The combined implant-abutments were individually placed in tubes containing the CaSaB culture medium and incubated in a bacteriological constant temperature oven for 14 days. The samples were observed daily as to the presence of turbidity, and after the designated time the microorganisms were collected from the implant interiors and analyzed by the two methods. RESULTS: After 14 days, six implant-abutment assemblies showed turbidity. Both methods indicated reduced microorganism counts in samples from the interior of the implant-abutment assemblies after incubation in the culture medium; however, the number of counts of F. nucleatum was higher by the DNA Checkerboard method when compared to the group analyzed by conventional bacterial cultures (p < 0.05). CONCLUSION: The DNA Checkerboard method was shown to be more sensitive than conventional cultures in the detection of microorganisms.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".