Itaconate-producing neutrophils regulate local and systemic inflammation following trauma
Bibliographic record
Abstract
Modulation of the immune response to initiate and halt the inflammatory process occurs both at the site of injury as well as systemically. Due to the evolving role of cellular metabolism in regulating cell fate and function, tendon injuries that undergo normal and aberrant repair were evaluated by metabolic profiling to determine its impact on healing outcomes. Metabolomics revealed an increasing abundance of the immunomodulatory metabolite itaconate within the injury site. Subsequent single-cell RNA-Seq and molecular and metabolomic validation identified a highly mature neutrophil subtype, not macrophages, as the primary producers of itaconate following trauma. These mature itaconate-producing neutrophils were highly inflammatory, producing cytokines that promote local injury fibrosis before cycling back to the bone marrow. In the bone marrow, itaconate was shown to alter hematopoiesis, skewing progenitor cells down myeloid lineages, thereby regulating systemic inflammation. Therapeutically, exogenous itaconate was found to reduce injury-site inflammation, promoting tenogenic differentiation and impairing aberrant vascularization with disease-ameliorating effects. These results present an intriguing role for cycling neutrophils as a sensor of inflammation induced by injury - potentially regulating immune cell production in the bone marrow through delivery of endogenously produced itaconate - and demonstrate a therapeutic potential for exogenous itaconate following tendon injury.
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 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 | 0.000 |
| 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".