Biphasic Vesicles for Topical Delivery of Interferon Alpha in Human Volunteers and Treatment of Patients with Human Papillomavirus Infections
Bibliographic record
Abstract
PURPOSE. Topical biphasic vesicle delivery system encapsulating interferon alpha (IFN α) was developed as an alternative to injections used to treat human papillomavirus (HPV) infections. METHODS. Biphasic lipid vesicles encapsulating increasing doses of IFN α (biphasic IFN α) were characterized for encapsulation efficiency, size, zeta potential and vesicle structure by centrifugation, dynamic light scattering, confocal microscopy and small-angle x-ray scattering. Biphasic IFN-α delivery into human skin in vivo and topical efficacy in patients with genital warts were evaluated. RESULTS. Average encapsulation efficiency of IFN α was 81-91%. The average particle size was 1000-1100 nm and zeta potential +70 to +78 mV. After application of 5, 15 and 40MU/g biphasic IFN α formulation in a topical patch on the upper inner arm in healthy volunteers, skin IFN α levels increased to 120±30, 380±60 and 400±80 IU/mg protein in skin homogenates (n=5, 5, and 7), respectively. Topical application of biphasic IFN α (1 MU/dose) twice daily for two weeks in a pilot study with 12 patients with external condylomata acuminata resulted in a decrease in lesion size, in 2',5'-oligoadenylate synthetase activity and in tissue viral load. CONCLUSIONS. Biphasic vesicles delivered clinically significant levels of IFN α across intact human skin and elicited marked therapeutic effect in patients.
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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".