The role of protease inhibitors on the remineralization of demineralized dentin using the PILP method
Bibliographic record
Abstract
Mineralized and sound dentin matrices contain inactive preforms of proteolytic enzymes that may be activated during the demineralization cycle. In this study, we tested the hypothesis that protease inhibitors (PI) preserve demineralized collagen fibrils and other constituents of the dentin matrix and thereby affect the potential for remineralization. Artificial carious lesions with lesion depths of 140 μm were created with acetate buffer (pH = 5.0, 66 hours), and remineralized using a polymer-induced-liquid-precursor (PILP) process (pH = 7.4, 14 days) containing poly(aspartic acid) (pAsp) as the process-directing agent. De- and remineralizing procedures were performed in the presence or absence of PI. Ultrastructure and mechanical recovery of demineralized dentin following PILP remineralization were examined and measured in water with atomic force microscopy (AFM) and nanoindentation. Nanomechanical properties of hydrated artificial lesions had a low elastic modulus (ER <0.4 GPa) extending about 100 μm into the lesion, followed by a sloped region of about 140 μm depth where values reached those of normal dentin (18.0-20.0 GPa). Mapping of mineral content by both micro-FTIR and micro x-ray computed tomography correlated well with modulus profiles obtained by nanoindentation. Tissue demineralized in the presence of PI exhibited higher elastic moduli (average 2.8 GPa) across the lesion and comprised a narrow zone in the outer lesion with strongly increased modulus (up to 8 GPa; p < 0.05), which might be related to the preservation of non-collagenous proteins that appear to induce calcium phosphate mineral formation even under demineralizing physical-chemical conditions. However, mechanical aspects of remineralization through the elastic modulus change, and the micromorphological aspects with SEM and TEM observation were almost identical with PILP treatments being conducted in the presence or absence of PI. Thus, the application of the protease inhibitors (PI) seemed to be less effective in promoting the remineralization of demineralized dentin.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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".