086 Skin Wound Healing in Red Duroc X Yorkshire F1 Pigs: Effect of Wound Depth on Gene Expression
Bibliographic record
Abstract
Previous investigations have demonstrated that cutaneous healing in red Duroc pigs (RD) differs from healing in Yorkshire pigs (Y). Specifically, RD animals heal with the formation of hypercontracted, hyperpigmented scars, features which are not observed in Y animals. Further, this abnormal scarring may be genetically mediated, as demonstrated by the partial transmission of this phenotype to RD × Y offspring (F1). To further determine the degree of transmission of this phenotype, this study examined the effect of wound depth upon the healing response of F1 animals. Ten full thickness (FT) and ten deep dermal (DD, 1.8 mm) skin wounds (2 cm × 2 cm) were created on the backs of juvenile female F1 animals (N = 8) using previously published procedures. Biopsies (4 mm) were taken from FT and DD wounds on days 14, 28, 42, 56, and 70. Samples were used for histology and molecular analysis using RT‐PCR. There were no detectable differences between the FT and DD wounds on the gross or histologic level. However on a molecular level, there were numerous differences between the FT and DD wounds. Several genes investigated demonstrated increased expression levels in the DD wounds as compared to the FT wounds. Further, DD wounds demonstrated a unique pattern of expression for several other genes that differed from that observed in either the F1 FT wounds or in any RD or Y wounds. Given that previous investigations have shown that FT and DD wounds are nearly identical within each of the RD and Y strains, this represents a novel finding. These results indicate that the healing phenotype of the F1 animals may be regulated both by genetics and by the wound size/depth, suggesting that human wound healing may be similarly influenced by genetics, wound depth and potentially, environmental factors. Funding provided by NSERC, CIHR.
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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 | 0.000 | 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) | 0.000 | 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".