Improved Scar in Postburn Patients Following Interferon-α2b Treatment Is Associated with Decreased Angiogenesis Mediated by Vascular Endothelial Cell Growth Factor
Bibliographic record
Abstract
Hypertrophic scar (HTS) after thermal injury is a dermal fibroproliferative disorder, which leads to considerable morbidity. Previous clinical studies from our laboratory have suggested that interferon-alpha2b (IFN-alpha2b) improves scar quality as a result of the suppression of fibroblast function. More recently, our work has demonstrated that the improvement of scar in patients with HTS after IFN-alpha2b treatment may be associated with a decreased number of fibrocytes and/or altered fibrocyte function. In this study, we report that the improvement of HTS after IFNalpha-2b treatment may be associated with a decrease in angiogenesis. Using immunohistochemistry, we demonstrate an increase in angiogenesis in HTS compared to normal skin, and also show an increase in the expression of vascular endothelial cell growth factor (VEGF) in HTS. Subsequently, we demonstrate a significant reduction in angiogenesis in HTS tissue from patients after treatment with systemic IFN-alpha2b. By using a [3H] thymidine incorporation assay, we demonstrate that IFN-alpha2b suppresses the proliferation of human umbilical vein endothelial cells (HUVECs) in a dose-dependent manner. In addition, IFN-alpha2b inhibits VEGF-induced proliferation and tube formation by using HUVECs. All these effects may be a result of the blocking of VEGF receptor expression on endothelial cells by IFN-alpha2b. Taken together with previous results, the present study suggests that the improvement of scar quality in HTS patients after IFN-alpha2b treatment may also be associated with decreased angiogenesis in HTS. The current in vitro results may provide some insights into the scar improvement that is seen with systemic IFN-alpha2b treatment.
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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".