The therapeutic potential of a <scp>C</scp>‐<scp>X</scp>‐<scp>C</scp> chemokine receptor type 4 (<scp>CXCR</scp>‐4) antagonist on hypertrophic scarring in vivo
Bibliographic record
Abstract
Effective prevention and treatment of hypertrophic scars (HTSs), a dermal form of fibrosis that frequently occurs following thermal injury to deep dermis, are unsolved significant clinical problems. Previously, we have found that stromal cell-derived factor 1/CXCR4 signaling is up-regulated during wound healing in burn patients and HTS tissue after thermal injury. We hypothesize that blood-borne mononuclear cells are recruited into wound sites after burn injury through the chemokine pathway of stromal cell-derived factor 1 and its receptor CXCR4. Deep dermal injuries to the skin are often accompanied by prolonged inflammation, which leads to chemotaxis of mononuclear cells into the wounds by chemokine signaling where fibroblast activation occurs and ultimately HTS are formed. Blocking mononuclear cell recruitment and fibroblast activation, CXCR4 antagonism is expected to reduce or minimize scar formation. In this study, the inhibitory effect of CXCR4 antagonist CTCE-9908 on dermal fibrosis was determined in vivo using a human HTS-like nude mouse model, in which split-thickness human skin is transplanted into full-thickness dorsal excisional wounds in athymic mice, where these wounds subsequently develop fibrotic scars that resemble human HTS as previously described. CTCE-9908 significantly attenuated scar formation and contraction, reduced the accumulation of macrophages and myofibroblasts, enhanced the remodeling of collagen fibers, and down-regulated the gene and protein expression of fibrotic growth factors in the human skin tissues. These findings support the potential therapeutic value of CXCR4 antagonist in dermal fibrosis and possibly other fibroproliferative disorders.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".