Glutaraldehyde-induced porcine model mimics human chronic wounds: insights into pathophysiology and therapeutic applications
Bibliographic record
Abstract
Chronic wounds present a significant clinical challenge due to their complex pathophysiology and resistance to standard treatments. A key obstacle in developing therapies is the lack of animal models that accurately mimic human chronic wound characteristics. Existing rodent models fail to replicate critical features, such as delayed re-epithelialization and unresolved inflammation, while larger animals, including porcine models, also fall short. Here, we introduce a novel glutaraldehyde-induced porcine model that mimics key aspects of human chronic wounds. Glutaraldehyde causes dermal toxicity, resulting in impaired structural integrity, oxidative stress, persistent inflammation, and bacterial colonization. Analyses showed features such as delayed healing, extracellular matrix (ECM) disruption, mitochondrial dysfunction, and chronic inflammatory responses. Comparative transcriptomic and lipidomic studies revealed shared signaling pathways and metabolite profiles with human venous leg and diabetic foot ulcers, highlighting the translational relevance of the model. This innovative platform offers valuable insights into chronic wound mechanisms and aids the development of effective targeted therapies.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".