Transgenic mice overexpressing <scp>CD</scp>109 in the epidermis display decreased inflammation and granulation tissue and improved collagen architecture during wound healing
Bibliographic record
Abstract
Transforming growth factor-β (TGF-β) is a multifunctional growth factor involved in all aspects of wound healing. TGF-β accelerates wound healing, but an excess of its presence at the wound site has been implicated in pathological scar formation. Our group has recently identified CD109, a glycophosphatidylinositol-anchored protein, as a novel TGF-β coreceptor and inhibitor of TGF-β signaling in vitro. To determine the effects of CD109 in vivo on wound healing, we generated transgenic mice overexpressing CD109 in the epidermis. In excisional wounds, we show that CD109 transgenic mice display markedly reduced macrophage and neutrophil recruitment, granulation tissue area, and decreased Smad2 and Smad3 phosphorylation, whereas wound closure remains unaffected as compared with wild-type littermates. Futhermore, we demonstrate that the expression of the proinflammatory cytokines interleukin-1α and monocyte chemoattractant protein-1, and extracellular matrix components is markedly decreased during wound healing in CD109 transgenic mice. In incisional wounds, CD109 transgenic mice show improved dermal architecture, whereas the tensile strength of the wound remains unchanged. Taken together, our findings demonstrate that CD109 overexpression in the epidermis reduces inflammation and granulation tissue area and improves collagen organization in vivo.
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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".