12/15-lipoxygenase orchestrates murine wound healing via PPARγ-activating oxylipins acting holistically to dampen inflammation
Bibliographic record
Abstract
12/15-lipoxygenase (12/15-LOX, Alox15 ) generates bioactive oxygenated lipids during inflammation, however its homeostatic role(s) in normal healing are unclear. Here, the role of 12/15-LOX in resolving skin wounds was elucidated, focusing on how its lipids act together in physiologically relevant amounts. In mice, wounding caused acute appearance of 12/15-LOX-expressing macrophages and stem cells, coupled to early generation of ~12 monohydroxy-oxylipins and enzymatically oxidized phospholipids (eoxPL). Alox15 deletion increased collagen deposition, stem cell/fibroblast proliferation, IL6/pSTAT3, pSMAD3, and interferon (IFN)-γ levels. Conversely, CD206 expression, F480+ cells, and MMP9 and MMP2 activities were reduced. Alox15 −/− skin was deficient in PPARγ/adiponectin activity. Furthermore, while pro-inflammatory genes were upregulated as normal during wounding, many including Il6, Il1b, ccl4, Cd14, Cd274, Clec4d, Clec4e, Csf3, Cxcl2, and miR-21 failed to revert to baseline during healing, indicating disruption of PPARγ’s anti-inflammatory brake on NLRP3/inflammasome and TGF-β signaling. Reconstituting Alox15 −/− wounds with a physiological mixture of Alox15 -derived primary oxylipins generated by healing wounds restored MMP and dampened collagen deposition. The oxylipin mixture activated the PPARγ response element in vitro, while in vivo, its coactivator, Helz2 , was significantly upregulated as well as several fatty acid and prostaglandin PPARγ ligands. Additional inflammatory and proliferative gene networks impacted by Alox15 −/− included Elf4, Cebpb , and Tcf3. In summary, 12/15-LOX generates abundant monohydroxy oxylipins that act together via PPARγ. The identification of multiple gene alterations reveals several targets for treating nonhealing wounds. Our studies demonstrate that 12/15-LOX oxylipins act in concert, dampening inflammation in vivo, revealing the need to consider lipid signaling holistically.
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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".