STING coordinates resolution of inflammation during wound repair by modulating macrophage trafficking through STAT3
Bibliographic record
Abstract
Efficient cutaneous wound healing requires a coordinated transition between inflammatory phases mediated by dynamic changes in leukocyte subset populations. Here, we identify STING as a key innate immune mediator governing timely resolution of inflammation by regulating macrophage dynamics during skin repair. Using a mouse model, we show STING deficiency caused delayed wound closure associated with abnormal persistence of TNF-α+ leukocytes. This resulted from the impaired macrophage recruitment. STING controlled the trafficking of bone marrow myeloid cells into blood and wounds, intrinsically enhancing macrophage migratory capacity through STAT3 activation. Specifically, STING modulated the production of monocyte chemokines and their receptors CCR2/CCR5 to enable efficient egress and wound infiltration. Consequently, disrupted systemic and local STING-STAT3-chemokine signaling combine to delay macrophage influx. This study elucidates STING as a critical rheostat tuning macrophage responses through STAT3 to orchestrate inflammatory resolution necessary for efficient wound healing. Our findings have broad implications for targeting STING therapeutically in both regenerative medicine and inflammatory disease contexts.
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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".