In Vivo Assessment of Protease Dynamics in Cutaneous Wound Healing by Degradomics Analysis of Porcine Wound Exudates
Bibliographic record
Abstract
Proteases control complex tissue responses by modulating inflammation, cell proliferation and migration, and matrix remodeling. All these processes are orchestrated in cutaneous wound healing to restore the skin's barrier function upon injury. Altered protease activity has been implicated in the pathogenesis of healing impairments, and proteases are important targets in diagnosis and therapy of this pathology. Global assessment of proteolysis at critical turning points after injury will define crucial events in acute healing that might be disturbed in healing disorders. As optimal biospecimens, wound exudates contain an ideal proteome to detect extracellular proteolytic events, are noninvasively accessible, and can be collected at multiple time points along the healing process from the same wound in the clinics. In this study, we applied multiplexed Terminal Amine Isotopic Labeling of Substrates (TAILS) to globally assess proteolysis in early phases of cutaneous wound healing. By quantitative analysis of proteins and protein N termini in wound fluids from a clinically relevant pig wound model, we identified more than 650 proteins and discerned major healing phases through distinctive abundance clustering of markers of inflammation, granulation tissue formation, and re-epithelialization. TAILS revealed a high degree of proteolysis at all time points after injury by detecting almost 1300 N-terminal peptides in ∼450 proteins. Quantitative positional proteomics mapped pivotal interdependent processing events in the blood coagulation and complement cascades, temporally discerned clotting and fibrinolysis during the healing process, and detected processing of complement C3 at distinct time points after wounding and by different proteases. Exploiting data on primary cleavage specificities, we related candidate proteases to cleavage events and revealed processing of the integrin adapter protein kindlin-3 by caspase-3, generating new hypotheses for protease-substrate relations in the healing skin wound in vivo. The data have been deposited to the ProteomeXchange Consortium with identifier PXD001198.
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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) | 0.001 | 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 | 0.000 | 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".