The Biology of Extracellular Matrix Proteins in Hypertrophic Scarring
Bibliographic record
Abstract
Significance: Hypertrophic scars (HTS) are a fibroproliferative disorder that occur following deep dermal injury and affect up to 72% of burn patients. These scars result in discomfort, impaired mobility, disruption of normal function and cosmesis, and significant psychological distress. Currently, there are no satisfactory methods to treat or prevent HTS, as the cellular and molecular mechanisms are complex and incompletely understood. This review summarizes the biology of proteins in the dermal extracellular matrix (ECM), which are involved in wound healing and hypertrophic scarring. Recent Advances: New basic research continues toward understanding the diversity of cellular and molecular mechanisms of normal wound healing and hypertrophic scarring. Broadening the understanding of these mechanisms creates insight into novel methods for preventing and treating HTS. Critical Issues: Although there is an abundance of research conducted on collagen in the ECM and its relationship to HTS, there is a significant gap in understanding the role of proteoglycans and their specific isoforms in dermal fibrosis. Future Directions: Exploring the biological roles of ECM proteins and their unique isoforms in HTS, mature scars, and normal skin will further the understanding of abnormal wound healing and create a more robust understanding of what constitutes dermal fibrosis. Research into the biological roles of ECM protein isoforms and their regulation during wound healing warrants a more extensive investigation to identify their distinct biological functions in cellular processes and outcomes.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".