Photo-curing hyaluronic acid-Janus antibacterial packs as O2 generator precisely modulate the infectious microenvironment for antibiotic-free periodontal therapy
Bibliographic record
Abstract
Periodontal disease stands the leading cause of tooth loss in adults. While scaling and root planning is considered the “gold standard” treatment, it is often insufficient in efficiently eliminating anaerobic bacteria from deep periodontal pockets. In this work, an antibiotic-free and photo-curing hyaluronic acid-Janus (H-Janus) antibacterial pack was developed to inhibit the growth and colonization of residual bacteria within the pockets for reducing the recurrence of periodontitis. Our results demonstrated that a 4 wt% precursor solution of the antibacterial packs could be molded into various shapes by exposure to UV irradiation for less than 1 min, allowing the packs to seamlessly fill the irregular spaces of periodontal pockets. In vitro studies showed that the antibacterial packs gradually released lauric acid and oxygen over 7 days, exhibiting significant anti-biofilm effects against both aerobic and anaerobic bacteria. Notably, animal experiments confirmed that H-Janus antibacterial packs markedly improved the clinical scores in rats with periodontitis by inhibiting bacterial growth, alleviating inflammation, and fostering the regeneration of periodontal tissues. In light of their precise elimination of bacterial colonization and modulation of the infectious microenvironment, the H-Janus antibacterial packs show promising therapeutic potential for preventing the recurrence of periodontal pathogens following scaling and root planning. Scheme 1. Illustration of photo-curing H-Janus antibacterial packs precisely inhibiting microbial growth and modulating the infectious microenvironment for antibiotic-free periodontal therapy.
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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".