Reactivity of aragonite with dicalcium phosphate facilitates removal of dental calculus
Bibliographic record
Abstract
Dental calculus, a main contributor of periodontal diseases, is mostly composed of inorganic calcium phosphate species such as dicalcium phosphate, whitlockite, octa calcium phosphate, and hydroxyapatite. Under physiological pH 7.4, dicalcium phosphates can gradually interact with calcium carbonate to form hydroxyapatite. Therefore, we hypothesized that aragonite (Arg) could react with dental calculus, facilitating its removal. To assess the reactivity of Arg with dental calculus, we examined the changes in surface morphology, composition, and topography of Arg and dental calculus upon exposure to each other in an aqueous environment. The impact of Arg on the removal of dental calculus was assessed by brushing polished sections of dental calculus, enamel, and dentin with slurries of Arg and measuring the depth of abrasion using a stylus profilometer. Our results demonstrate that Arg can react with dental calculus in aqueous environment. This reaction increases calculus surface roughness which in turn facilitate dental calculus removal by brushing. Aragonite could be a promising abrasive for toothpaste design for management of dental calculus.
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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".