The pig as a model system for investigating the recruitment and contribution of myofibroblasts in skin healing
Bibliographic record
Abstract
In the skin-healing field, porcine models are regarded as a useful analogue for human skin due to their numerous anatomical and physiological similarities. Despite the widespread use of porcine models in skin healing studies, the initial origin, recruitment and transition of fibroblasts to matrix-secreting contractile myofibroblasts are not well defined for this model. In this review, we discuss the merit of the pig as an animal for studying myofibroblast origin, as well as the challenges associated with assessing their contributions to skin healing. Although a variety of wound types (incisional, partial thickness, full thickness, burns) have been investigated in pigs in attempts to mimic diverse injuries in humans, direct comparison of human healing profiles with regards to myofibroblasts shows evident differences. Following injury in porcine models, which often employ juvenile animals, myofibroblasts are described in the developing granulation tissue at 4 days, peaking at Days 7-14, and persisting at 60 days post-wounding, although variations are evident depending on the specific pig breed. In human wounds, the presence of myofibroblasts is variable and does not correlate with the age of the wound or clinical contraction. Our comparison of porcine myofibroblast-mediated healing processes with those in humans suggests that further validation of the pig model is essential. Moreover, we identify several limitations evident in experimental design that need to be better controlled, and standardisation of methodologies would be beneficial for the comparison and interpretation of results. In particular, we discuss anatomical location of the wounds, their size and depth, as well as the healing microenvironment (wet vs. moist vs. dry) in pigs and how this could influence myofibroblast recruitment. In summary, although a widespread model used in the skin healing field, further research is required to validate pigs as a useful analogue for human healing with regards to myofibroblasts.
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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) | 0.001 | 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".