A Histological Study of a Novel Pneumatic-Mechanical Microneedle-Assisted Topical Cutaneous Delivery System
Bibliographic record
Abstract
BACKGROUND: Device-assisted drug delivery (DADD) involves a device modality that facilitates the penetration of topical substances across the intact stratum corneum barrier. OBJECTIVE: This study analyzes the efficacy of a novel pneumatic-mechanical microneedle tip technology ("fusion tip") in assisting the transcutaneous delivery of fibroblast-stimulating substances including small particle hyaluronic acid (SPHA), large particle hyaluronic acid (LPHA), calcium hydroxylapatite (CaHA), and poly-L-lactic acid (PLLA). METHODS MATERIALS: The subject was a 34-year-old otherwise healthy woman. Subject abdominal skin preplanned for subsequent abdominoplasty was treated with pneumatic-mechanical and sham control tips in test spots to topically deliver liquid SPHA, LPHA, CaHA, and PLLA at 0.5 and 2.5 mm treatment depths. Immediately after and 1 week post-treatment, 3 mm punch biopsies were obtained for histological analysis. RESULTS: All substances showed demonstrable drug delivery with both tips except LPHA. Deeper needle depths improved delivery. The pneumatic-mechanical tip enhanced delivery of SPHA and PLLA both immediately postprocedure and at the 7-day follow-up. Calcium hydroxylapatite delivery was similar between the 2 tips, other than increased delivery at 0.5 mm depth immediately postprocedure with the pneumatic-mechanical tip. CONCLUSION: Microneedling is an effective method of DADD, with the pneumatic-mechanical tip improving delivery for most test substances.
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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".