Proteomic Evaluation of Acquired Enamel Pellicle during In Vivo Formation
Bibliographic record
Abstract
Acquired enamel pellicle (AEP) is a protein film that forms on the enamel surface of teeth by selective adsorption of proteins and peptides present in the mouth. This protein film forms the interface between enamel and the damage oral biofilm, which modulates the attachment of bacteria found in oral biofilm. The overall goal of this study was to gain insight into the biological formation of the human in vivo AEP. This study hypothesized that AEP is created by the formation of successive protein layers, which consist of initial binding to enamel and subsequent protein-protein interactions. This hypothesis was examined by observing quantitative and qualitative changes in pellicle composition during the first two hours of AEP formation in the oral cavity. Quantitative mass spectrometry approaches were used to generate an AEP protein profile for each time-point studied. Relative proteomic quantification was carried out for the 50 proteins observed in all four time-points. Notably, the abundance of important salivary proteins, such as histatin 1, decrease with increasing of the AEP formation, while other essential proteins such as statherin showed constant relative abundance in all time-points. In summary, this is the first study that investigates the dynamic process to the AEP formation by using proteomic approaches. Our data demonstrated that there are significant qualitative and quantitative proteome changes during the AEP formation, which in turn will likely impact the development 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".