Differential susceptibility to lethal endotoxaemia in mice deficient in IL‐1α, IL‐1β or IL‐1 receptor type I
Bibliographic record
Abstract
The role of intereukin-1 (IL-1) in mortality caused by endotoxaemia remains controversial. While IL-1 receptor antagonist (IL-1Ra) protects mice from lethal endotoxaemia, mice deficient in IL-1β (IL-1β⁻( /)⁻) display normal susceptibility to lipopolysaccharide (LPS). The aim of this study was to identify the source of these discrepancies. Mice deficient in IL-1α, IL-1β or IL-1R type I were injected intraperitoneally with Escherichia coli or Salmonella typhimurium LPS. Survival of the mice was examined and compared with C57/Bl6 wild-type mice. In addition, serum cytokine concentrations were determined after LPS challenge and in vitro cytokine production by peritoneal macrophages was analysed. Clearance of radioactive IL-1α was examined in IL-1α⁻(/)⁻ and wild-type mice. IL-1β⁻(/)⁻ mice were normally susceptible to endotoxaemia and cytokine production did not differ from that in control mice. Surprisingly, LPS mortality in IL-1α⁻(/)⁻ mice was significantly greater than that in control mice, accompanied by higher interferon-γ release. These effects were mediated by a distorted homeostasis of IL-1RI receptors, as shown by a strongly delayed clearance of IL-1α. In contrast to the IL-1α⁻(/)⁻ and IL-1β⁻(/)⁻ mice, IL-1RI⁻(/)⁻ mice were completely resistant to high doses of LPS. In conclusion, IL-1RI-mediated signals are crucial in mediating mortality occurring as a result of lethal endotoxaemia. Investigation of IL-1-mediated pathways in IL-1 knock-out mice is complicated by a distorted homeostasis of IL-1Rs.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".