Serum Decorin, Interleukin-1β, and Transforming Growth Factor-β Predict Hypertrophic Scarring Postburn
Bibliographic record
Abstract
Hypertrophic scar after burn injury is a significant problem. Previous studies have examined the roles for decorin, interleukin-1β, and transforming growth factor-β1 in hypertrophic scar formation locally, but few have considered their systemic influence. The authors conducted a pilot study to examine whether serum levels of these molecules could predict hypertrophic scar formation. Serum levels were measured using enzyme-linked immunosorbent assay, and hypertrophic scar formation determined from chart reviews. Peripheral blood mononuclear cells and fibroblasts were stimulated with decorin, interleukin-1β, and transforming growth factor-β1, and expression of profibrotic molecules examined using flow cytometry, immunofluorescence microscopy, quantitative polymerase chain reaction, and mass spectrometry. Multiple linear regression analysis suggested early serum levels of decorin and interleukin-1β, and late serum levels of transforming growth factor-β1 were predictive of hypertrophic scar formation. Decorin up-regulated the expression of toll-like receptor 4 and C-X-C receptor 4 in peripheral blood mononuclear cells, and interleukin-1β up-regulated fibroblast production of C-X-C ligand 12. Transforming growth factor-β1 up-regulated, and interleukin-1β down-regulated, the production of profibrotic cytokines, collagen, and myofibroblast differentiation. The model predicting hypertrophic scar formation is supported by clinical results and limited in vitro experiments.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| 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".