A Preliminary Report of the Biochemical and Clinical Effects of 1,4-Diaminobutane on Prevention of Human Hypertrophic Scars
Bibliographic record
Abstract
Objective evidence for the role of inhibition of collagen cross-linking in human scar using a nontoxic topical inhibitor, 1,4-diaminobutane (1,4 DAB), in patients with scars at risk for hypertrophic scar formation is presented. The authors used a concentration of 1,4 DAB of 0.8% (weight/volume) in a cream base similar to Glaxal Base. Application was once per day at night. The control was treated with cream base alone. In treatment phase studies at 2 months, tissue biopsies were performed and used to determine a therapeutic effect biochemically in paired scars harvested chosen with typical hypertrophic scars at two major treatment centers. Tissue transglutaminase activity revealed a significant reduction of the ε-(γ-glutamyl)lysine cross-links in the treated scars: 7.96 ± 1.51 pmol/µmol amino acid versus 14.78 ± 3.52 pmol/µmol amino acid. A subset of paired scars (n = 15) was also analyzed for soluble procollagen type III amino propeptide. The effect was a significant increase in procollagen type III amino propeptide in the scars treated with 1,4 DAB compared with sham-treated scars: 47.75 ± 4.6 µg/mg wet weight versus 39.08 ± 6.02 µg/mg wet weight, respectively. Levels of tissue 1,4 DAB was found to be twice as high in the presence of the active cream versus in the tissue of the control group. In subsequent prophylaxis studies, the authors treated 44 breast reduction patients prospectively with active cream to one or the other side in a double-blind randomized fashion. Hardness (in grams) measured using a Rex Durometer at 6 and 12 weeks postoperatively along with photographs were analyzed. The mean value ± SD of 24.98 ± 1.2 g on the active side versus 31.76 ± 1.1 g on the sham side was significantly different (p < 0.05). The patient scale scores of the Patient and Observer Scar Assessment Scale were also requested by survey in a responding 27-patient subgroup at a minimum 1 year postoperatively, and the differences between the two sides were found to be statistically significant, where the mean on the active side was 14.07 ± 1.34 and the mean on the sham side was 21.41 ± 1 (p < 0.05). The results are evidence to support the use of this agent in prevention of hypertrophic scars. CLINICAL QUESTION/LEVEL OF EVIDENCE:: Therapeutic, II.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".