Epigallocatechin-3-gallate/mineralization precursors co-delivery hollow mesoporous nanosystem for synergistic manipulation of dentin exposure
Bibliographic record
Abstract
As a global public health focus, oral health plays a vital role in facilitating overall health. Defected teeth characterized by exposure of dentin generally increase the risk of aggravating oral diseases. The exposed dentinal tubules provide channels for irritants and bacterial invasion, leading to dentin hypersensitivity and even pulp inflammation. Cariogenic bacterial adhesion and biofilm formation on dentin are responsible for tooth demineralization and caries. It remains a clinical challenge to achieve the integration of tubule occlusion, collagen mineralization, and antibiofilm functions for managing exposed dentin. To address this issue, an epigallocatechin-3-gallate (EGCG) and poly(allylamine)-stabilized amorphous calcium phosphate (PAH-ACP) co-delivery hollow mesoporous silica (HMS) nanosystem (E/[email protected]) was herein developed. The application of E/[email protected] effectively occluded the dentinal tubules with acid- and abrasion-resistant stability and inhibited the biofilm formation of Streptococcus mutans. Intrafibrillar mineralization of collagen fibrils and remineralization of demineralized dentin were induced by E/[email protected] The odontogenic differentiation and mineralization of dental pulp cells with high biocompatibility were also promoted. Animal experiments showed that E/[email protected] durably sealed the tubules and inhibited biofilm growth up to 14 days. Thus, the development of the E/[email protected] nanosystem provides promising benefits for protecting exposed dentin through the coordinated manipulation of dentin caries and hypersensitivity.
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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".