Preclinical Models of Wound Healing: Is Man the Model? Proceedings of the Wound Healing Society Symposium
Bibliographic record
Abstract
Significance: A review of therapeutic effects in preclinical and clinical studies suggests that concordance between large animal (pig=78%), small laboratory animal (53%) and in vitro (57%) results with those observed in humans is only partial. Pig models of wound healing provide major advantages over other animal models. Since the vast majority of wound-healing research is done in rodents and in vitro, the low concordance rate is a significant impediment to research that will have any clinical impact. Critical Issues: To generate clinically relevant experimental data, hypothesis generation should begin, or at least involve human wound tissue samples. Such tissue could be used to test a predetermined hypothesis generated based on, say, murine data. Alternatively, such tissue could be analyzed using high-throughput cell biology techniques (e.g., genomics, proteomics, or metabolomics) to identify novel mechanisms involved in human wounds. Once the hypothesis has been formulated and confirmed using human samples, identification of these same mechanisms in animals represents a valid approach that could be used for more in-depth investigations and experimental manipulations not feasible with humans. Future Directions: This consensus statement issued by the Wound Healing Society symposium strongly encourages all wound researchers to involve human wound tissue validation studies to make their animal and cell biology studies more translationally and clinically significant.
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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 | 0.001 |
| 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".