Quantitative Proteomic Analysis of the Effect of Fluoride on the Acquired Enamel Pellicle
Bibliographic record
Abstract
The acquired enamel pellicle (AEP) is a thin film formed by the selective adsorption of salivary proteins onto the enamel surface of teeth. The AEP forms a critical interface between the mineral phase of teeth (hydroxyapatite) and the oral microbial biofilm. This biofilm is the key feature responsible for the development of dental caries. Fluoride on enamel surface is well known to reduce caries by reducing the solubility of enamel to acid. Information on the effects of fluoride on AEP formation is limited. This study aimed to investigate the effects of fluoride treatment on hydroxyapatite on the subsequent formation of AEP. In addition, this study pioneered the use of label-free quantitative proteomics to better understand the composition of AEP proteins. Hydroxyapatite discs were randomly divided in 4 groups (n = 10 per group). Each disc was exposed to distilled water (control) or sodium fluoride solution (1, 2 or 5%) for 2 hours. Discs were then washed and immersed in human saliva for an additional 2 hours. AEP from each disc was collected and subjected to liquid chromatography electrospray ionization mass spectrometry for protein identification, characterization and quantification. A total of 45 proteins were present in all four groups, 12 proteins were exclusively present in the control group and another 19 proteins were only present in the discs treated with 5% sodium fluoride. Relative proteomic quantification was carried out for the 45 proteins observed in all four groups. Notably, the concentration of important salivary proteins, such as statherin and histatin 1, decrease with increasing levels of fluoride. It suggests that these proteins are repulsed when hydroxyapatite surface is coated with fluoride. Our data demonstrated that treatment of hydroxyapatite with fluoride (at high concentration) qualitatively and quantitatively modulates AEP formation, effects which in turn will likely impact the formation of oral biofilms.
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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".