Calcium and fluoride interaction in human enamel at nanoscale: an XPS assessment
Bibliographic record
Abstract
Objective This research aimed to assess qualitatively and quantitatively the penetration depth of fluoride ions on nanosurface enamel (30 nm). Topical fluoride application reduces acid erosion on tooth enamel, which is the main contributing factor to tooth decay and dental caries. Our goal is to study the mechanics of chemically reacting free fluoride into the CaP crystals in the enamel's first atomic layers. Materials and Methods Unerupted third molars were randomly selected, and enamel tooth samples were fragmented. Two fluoridated agents (gel and foam; APF 1.23% F ion) were used: at two application times (1 and 4 min; n-6). X-ray photoelectron spectroscopy (XPS) technique was utilized to characterize the enamel nanosurface of the samples to a profile depth of 0, 10, 20, and 30 nanometers. Statistical analysis using three-way ANOVA (factors: agent, time, and depth) was performed on the results (α = 0.05) Results There was a statistically significant difference between the control and the fluorinated surfaces ( p = 0). However, factor time was not significantly different ( p = 0.47), and in the same way, its interaction with the factors APF agent ( p = 0.16). Factor depth was significantly different ( p = 2.29×10 −11 ).The highest atomic percentage of elemental fluoride was discovered within the surface layers of enamel at a profile depth of 10 nm for both application times and either fluoridated agent. This study showed that CaF 2 -like is formed mainly by substituting CaOH than HAp in the first layers of enamel (30 nm depth). Conclusion This research has demonstrated that fluoride ions stay in a very superficial layer of enamel regardless of application time and or the APF agent utilized. This information is critical to understanding the demineralization and remineralization processes.
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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) | 0.002 | 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".