Molecular, histologic, and gross phenotype of skin wound healing in red Duroc pigs reveals an abnormal healing phenotype of hypercontracted, hyperpigmented scarring
Bibliographic record
Abstract
This study examined dermal wound healing in juvenile red Duroc pigs and determined that these animals exhibit a unique healing phenotype at multiple levels. Gross and histologic analysis revealed that full-thickness and deep dermal (1.8 mm deep) wounds both heal via formation of hypercontracted, hyperpigmented scars. Molecular analysis using reverse-transcriptase polymerase chain reaction and porcine-specific primer sets revealed that types I and III collagen, heat shock protein 47, bone morphogenetic protein-1, several proteoglycans, and tissue inhibitor of metalloproteinases 1-3 all showed a unique biphasic pattern of mRNA expression compared to previous results with Yorkshire pigs. This pattern was characterized by an initial peak of expression early after wounding, followed by a return to near-normal levels by days 28-42, and then a second increase in mRNA levels at days 56-70. The second phase of increased gene expression correlated with an increased collagen deposition as observed by picrosirius red staining and polarizing light microscopy. Reverse-transcriptase polymerase chain reaction analysis also revealed a prolonged expression of matrix metalloproteinase-2 compared to previous findings in the Yorkshire strain. Further characterization of the genetics and molecular biology associated with the red Duroc phenotype may provide insight into aberrant human wound healing.
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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".