The Atypical Chemokine Receptor ACKR2 is Protective Against Sepsis
Bibliographic record
Abstract
Sepsis is a systemic inflammatory response as a result of uncontrolled infections. Neutrophils are the first cells to reach the primary sites of infection, and chemokines play a key role in recruiting neutrophils. However, in sepsis chemokines could also contribute to neutrophil infiltration to vital organs leading to multiple organ failure. ACKR2 is an atypical chemokine receptor, which can remove and degrade inflammatory CC chemokines. The role of ACK2 in sepsis is unknown. Using a model of cecal ligation and puncture (CLP), we demonstrate here that ACKR2 deficient () mice exhibited a significant reduction in the survival rate compared with similarly treated wild-type (WT) mice. However, neutrophil migration to the peritoneal cavity and bacterial load were similar between WT and ACKR2 mice during CLP. In contrast, ACKR2 mice showed increased neutrophil infiltration and elevated CC chemokine levels in the lung, kidney, and heart compared with the WT mice. In addition, ACKR2 mice also showed more severe lesions in the lung and kidney than those in the WT mice. Consistent with these results, WT mice under nonsevere sepsis (90% survival) had higher expression of ACKR2 in these organs than mice under severe sepsis (no survival). Finally, the lungs from septic patients showed increased number of ACKR2 cells compared with those of nonseptic patients. Our data indicate that ACKR2 may have a protective role during sepsis, and the absence of ACKR2 leads to exacerbated chemokine accumulation, neutrophil infiltration, and damage to vital organs.
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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) | 0.000 | 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) | 0.002 | 0.001 |
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".