Innate immune cells orchestrate the repair of sterile injury in the liver and beyond
Bibliographic record
Abstract
There is a close association between inflammation and sterile injury, however not all sterile injuries are the same. While a regulated inflammatory response is crucial for proper healing, a dysregulated or nonterminating response leads to disrepair. While immune cells are thought to contribute to the disrepair, they may also be critical for proper healing and as such, their actions may dictate the end result. In all forms of sterile injury, release of damage-associated molecular patterns from necrotic cells causes robust recruitment of innate immune cells. The subsequent release of toxic mediators from immune cells is thought to be damaging in non-resolving sterile injuries in which the dysregulated immune response leads to chronic inflammatory disease. While similar mediators may be released from immune cells in resolution of acute injury, the spatial localization, timing, and self-termination may all be critical. In this review, we summarize the recent advances in our understanding of the temporal and spatial recruitment of various innate immune cells that beget appropriate healing of acute injuries. Where possible we try to compare this appropriate response to dysregulated sterile injuries in an attempt to identify novel therapeutic targets.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".