The composition of the dental pellicle: an updated literature review
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Background: The dental pellicle is a thin layer of up to several hundred nm in thickness, covering the tooth surface. It is known to protect the teeth from acid attacks through its selective permeability and it is involved in the remineralization process of the teeth. It functions also as binding site and source of nutrients for bacteria and conditioning biofilm (foundation) for dental plaque formation. Methods: For this updated literature review, the PubMed database was searched for the dental pellicle and its composition. Results: The dental pellicle has been analyzed in the past years with various state-of-the art analytic techniques such as high-resolution microscopic techniques (e.g., scanning electron microscopy, atomic force microscopy), spectrophotometry, mass spectrometry, affinity chromatography, enzyme-linked immunosorbent assays (ELISA), and blotting-techniques (e.g., western blot). It consists of several different amino acids, proteins, and proteolytic protein fragments. Some studies also investigated other compounds of the pellicle, mainly fatty acids, and carbohydrates. Conclusions: The dental pellicle is composed mainly of different proteins, but also fatty acids, and carbohydrates. Analysis with state-of-the-art analytical techniques have uncovered mainly acidic proline-rich proteins, amylase, cystatin, immunoglobulins, lysozyme, and mucins as main proteins of the dental pellicle. The pellicle has protective properties for the teeth. Further research is necessary to gain more knowledge about the role of the pellicle in the tooth remineralization process.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it