Lidocaine-loaded dissolving microneedle for safe local anesthesia on oral mucosa for dental procedure
Bibliographic record
Abstract
BACKGROUND: Lidocaine has been widely used as a short-acting local anesthetic agent to reduce the pain caused by needle insertion. Dissolving microneedles (DMNs), which are minimally invasive, can effectively deliver drugs by overcoming the oral mucosal barrier and relieving patient discomfort. METHODS: Lidocaine solution prepared by mixing lidocaine-HCl and hyaluronic acid was used to fabricate oral lidocaine HCl-encapsulated DMNs (oral Li-DMNs) via centrifugal lithography. The dissolution, penetration ability, and local transmucosal drug delivery of oral Li-DMNs into the oral mucosa were evaluated in porcine jaws. Pharmacokinetic analysis and safety assessment were performed using rabbits. RESULTS: The insertion depth of the oral Li-DMNs satisfies the safety standard. The oral Li-DMNs were completely dissolved after 3 min of application. The local transmucosal drug delivery, pharmacokinetic, and safety evaluations showed that the oral Li-DMNs can obtain a local anesthesia effect at a relatively lower dose, and there was no oral mucosal irritation in rabbits. CONCLUSIONS: A novel and safe oral Li-DMNs have potential applications in large animals and clinical trials and would possibly enter the anesthesia market.
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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".