Degradative Activities of Human Neutrophils toward the Tooth, Restoration and Restoration-tooth Interface
Bibliographic record
Abstract
Human neutrophils constantly enter the mouth and release catabolic factors that are hypothesized to biodegrade the restoration, tooth and the restoration-tooth interface. Blood neutrophils were shown to have esterase-like and protease, matrix-metalloproteinase-like activities measured with colorimetric and fluorometric assays. Resin monomers, resin composite, resin adhesives, and tooth dentin were degraded by neutrophils in a material dependant manner, as measured by quantifying degradation by-products using ultra-performance-liquid-chromatography and imaged with scanning electron microscopy. Neutrophils also affected fracture toughness and fracture mode of restoration-tooth specimens compared to incubation with media alone. The above suggest a potential role of neutrophils in the development of primary and secondary caries, a significant health, and economic burden with more than 16 million restorations placed in Canada at a cost of $3B, mostly due to replacement of failed restorations. The development of materials and techniques to reduce degradation of restorations, restoration’s margins and tooth could enhance restoration longevity.
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.
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) | 0.004 | 0.001 |
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".