Effect of in vitro Acidification on Plaque Fluid Composition With and Without a NaF or a Controlled-release Fluoride Rinse
Bibliographic record
Abstract
Plaque fluid ion concentration changes, especially fluoride, in response to the pH decrease associated with a cariogenic episode are important components of the caries process. A "controlled-release" (CR) fluoride rinse, based on the controlled release of fluoride in the presence of calcium, has been shown to form large fluoride reservoirs in resting plaque. In this study, the in vitro acid-induced release of fluoride, and other ions, was examined in 48-hour-fasted plaque fluid from subjects (n = 11) who received no rinse, or who used a 228-ppm CR or NaF fluoride rinse 1 hr before being sampled. After collection, the plaque was centrifuged to yield plaque fluid, acidified (0.1 microL of 0.5 mol/L HCl per milligram plaque), and then re-centrifuged before a second sample was obtained. Although previous studies indicated a higher plaque fluid fluoride after the new rinse relative to NaF, no statistically significant difference was observed here. Average fluoride release after acidification (average pH, 5.2) was statistically greater following the use of the CR rinse (153 micromol/L) compared with the NaF rinse (17 micromol/L). No fluoride release was seen in the no-rinse samples. The pH, free calcium, phosphate, acetate, propionate, and buffer capacity were not affected by the different amounts of fluoride deposited in the plaque. However, following acid addition, an increase in free calcium and phosphate was observed, which was also independent of the rinse. The large release of fluoride following acidification suggests that the new rinse may provide an improved cariostatic effect.
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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) | 0.001 | 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".