Bidirectional crosstalk via IL‐6, PGE<sub>2</sub>and PGD<sub>2</sub>between murine myofibroblasts and alternatively activated macrophages enhances anti‐inflammatory phenotype in both cells
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Alternatively activated macrophages (AAMs) are important cells in the resolution of inflammation and tissue repair. We examined the impact of myofibroblasts, a vital cell in wound healing and tissue repair, on the development and function of AAMs. EXPERIMENTAL APPROACH: The interaction between AAMs and myofibroblasts was tested using conditioned medium from murine dermal myofibroblasts and bone marrow-derived macrophages. AAMs were differentiated with IL-4 and IL-13. KEY RESULTS: Conditioned medium from myofibroblasts enhanced the expression of AAM markers, arginase 1 and Ym1 (chitinase-3-like 3) and the spontaneous production of IL-10, while suppressing LPS-induced nitric oxide production. IL-6 from the myofibroblasts contributed to the amplification of the AAM phenotype; the selective COX-2 inhibitor, NS-398, significantly reduced the ability of myofibroblasts to promote an AAM phenotype. Pharmacological analyses indicated that myofibroblast-derived IL-6 enhanced arginase activity and spontaneous IL-10 output, while PGE2 , via the EP4 receptor, enhanced arginase expression and LPS-evoked IL-10 production. PGD2 suppressed LPS-evoked nitric oxide via the DP1 receptor. Reciprocally, conditioned medium from macrophages treated with IL-4 + IL-13 and myofibroblast conditioned medium components, but not macrophages given IL-4 + IL-13 only, reduced myofibroblast migration, the expression of COX-2, and the production of PGE2 and PGD2 . CONCLUSIONS AND IMPLICATIONS: These findings define mechanisms by which myofibroblasts enhance an AAM phenotype, which can promote wound healing directly, and/or via feedback communication to the myofibroblast, subsequently down-regulating its capacity to promote AAM function. This is an important homeostatic regulatory pathway in wound healing that can also limit unwanted fibrosis.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".