Accelerated wound healing in leukocyte-specific, protein 1-deficient mouse is associated with increased infiltration of leukocytes and fibrocytes
Bibliographic record
Abstract
Wound healing is a complex process involving the integrated actions of numerous cell types, soluble mediators, and ECM. Recently, a newly identified cell type, the fibrocyte, has been reported to contribute to wound healing and fibrotic conditions such as hypertrophic scarring. We previously established leukocyte-specific protein 1 (LSP1) as a marker for fibrocytes. LSP1 is an F-actin binding protein and substrate of p38 mitogen-activated protein kinase and protein kinase C, and has been reported to be important in leukocyte chemotaxis. We examine the biological roles of LSP1 in skin wound healing using Lsp1(-/-) null mice. These animals showed accelerated healing of full-thickness skin wounds, with increased re-epithelialization rates, collagen synthesis, and angiogenesis. Healing wounds in Lsp1(-/-) mice had higher densities of neutrophiles, macrophages, and fibrocytes. Along with increased leukocyte infiltration, levels of macrophage-derived chemokine expression, TGF-beta1, and VEGF were all up-regulated. These results demonstrate that the absence of LSP1 promotes healing of skin wounds. The primary mechanism seems to be an increase in leukocyte infiltration, leading to locally elevated synthesis and release of chemokines and growth factors. Further analysis of Lsp1(-/-) mice may suggest ways to improve wound healing and/or treat fibrotic conditions of skin and other tissue.
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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 | 0.001 | 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".