Lipocalin 2 confers protection against endotoxin‐induced sepsis in mice
Bibliographic record
Abstract
Sepsis is characterized by elevated systemic proinflammatory cytokines and agents that can act as amplifiers (HMGB1) or dampeners (sIL‐1Ra) of inflammation and thus play a decisive role in sepsis. Lipocalin 2 (Lcn2), which is upregulated by log orders of magnitude during inflammation but its role in sepsis, is largely unknown. Lcn2 deficient mice (Lcn2KO) and their WT littermates were given E. coli LPS (20mg/kg BW) i.p. and monitored for mortality. Serum TNFα, IL‐18 and aminotransferases were analyzed. Splenocyte apoptosis was assayed 24h after LPS by TUNEL staining, caspase 3 and flow cytometry. Peritoneal cells from WT and Lcn2KO mice were stimulated with LPS and cytokines, COX2 and iNOS were analyzed. In WT mice, LPS‐induced systemic Lcn2 peaked at 24h and returned to basal levels by 48h. All Lcn2KO died by day 8 while only 20% mortality was observed in WT mice. In addition, Lcn2KO exhibited substantial elevation of every parameter tested including both pro and anti‐inflammatory cytokines. Further, splenocytes exhibited extensive apoptosis as measured by caspase 3 and TUNEL staining. Flow cytometry revealed that apoptosis of neutrophils, CD3+CD4+ and dendritic cells were significantly increased in Lcn2KO. Our data demonstrate that Lcn2 is a host protective factor during sepsis and, given its multifunctionality, small size, and simple structure it may be developed as potential therapeutic agent to treat sepsis.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".