Silver microwires from treating tooth decay with silver diamine fluoride
Bibliographic record
Abstract
Abstract Silver diamine fluoride (SDF) is a brush-on treatment for tooth decay that stops 81% of cavitated caries lesions (dental cavities). Before this innovation, caries was treatable only with operative approaches (dental fillings). SDF-treated lesions harden and become resistant to further decay. We hypothesized that the hardening is due to reaction with silver, rather than classic fluoride-mediated remineralization, because infected dentin is not amenable to remineralization. Using synchrotron microCT with 1.3 μm resolution, we observe filamentous densities up to 500 μm in length and 0.25-7.0 μm in diameter, formed in situ by applying SDF to caries lesions. We show that these “microwires” fill voids in the lesion caused by disease, and permeate through surrounding dentinal tubules. Using spectroscopy, we confirm that the chemical composition of the observed microwires is predominantly silver. To our knowledge, this represents the first structural microscale observations resulting from clinical SDF treatment. These novel observations hint at mechanistic explanations for the first clinical method to harden carious dentin besides remineralization. We hypothesize that SDF may not only achieve its antimicrobial functions by biochemical interactions, but also through its inherent ability to integrate into dentin.
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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) | 0.000 | 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) | 0.001 | 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".