An Exploratory Study of PN HPT for Treating Postsurgical Atrophic and Depressed Scars
Bibliographic record
Abstract
BACKGROUND: Postsurgical atrophic scars tend to respond poorly to treatments, especially non-energy-based ones. Hydrophilic PN HPT (Polynucleotides High Purification Technology) injected intradermally is a non-energy-based option with an immediate volume-enhancing effect that indirectly improves the fibroblast synthesis of collagen and extracellular matrix. The PN HPT ingredient has the further benefit of a dermal "priming" effect that enhances the efficacy of other scar treatments. OBJECTIVES: Verify retrospectively, with advanced techniques, the efficacy of PN HPT monotherapy as postsurgical scar treatment. METHODS: Retrospective data collection in 18- to 65-year-old women with moderate-to-severe atrophic scars after mammary surgery undergoing a five-session intradermal treatment course with 0.75% PN HPT gel formulation in single-use syringes starting 6 months after surgery. Primary retrospective efficacy parameter: changes in scar morphology and symptom severity after three and 6 months (modified Vancouver Scar Scale, mVSS). Secondary efficacy parameters: roughness score 6 months after baseline (Antera 3D CS tridimensional skin analysis system) and Global Aesthetic Improvement Scale (GAIS, Investigator and Patient subscales) after three and 6 months. RESULTS: Total mean mVSS highly significantly improved from 11.2 ± 1.92 at baseline to 7.0 ± 1.68 and 6.9 ± 1.55 after three and 6 months, respectively; the mean Antera 3D CS roughness score improved from 13.5 ± 4.14 to 10.0 ± 3.49 after 6 months. After three and 6 months, the GAIS subscores for investigators and cohort subjects were identical (3.0 ± 0.81 and 3.0 ± 0.72, respectively). The photographic documentation supported the previous results. CONCLUSIONS: In monotherapy, the intradermal PN HPT ingredient seems to quickly and safely relieve the burden of postsurgical atrophic scars. However, the lack of a formal parallel control group is a severe limitation. The objective quantitative measurements confirmed the long-lasting benefits.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 teacher head, 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".