Liver is the major source of elevated serum lipocalin‐2 levels after bacterial infection or partial hepatectomy: A critical role for IL‐6/STAT3
Bibliographic record
Abstract
UNLABELLED: Lipocalin-2 (LCN2) was originally isolated from human neutrophils and termed neutrophil gelatinase-associated lipocalin (NGAL). However, the functions of LCN2 and the cell types that are primarily responsible for LCN2 production remain unclear. To address these issues, hepatocyte-specific Lcn2 knockout (Lcn2(Hep-/-)) mice were generated and subjected to bacterial infection (with Klesbsiella pneumoniae or Escherichia coli) or partial hepatectomy (PHx). Studies of Lcn2(Hep-/-) mice revealed that hepatocytes contributed to 25% of the low basal serum level of LCN2 protein (∼ 62 ng/mL) but were responsible for more than 90% of the highly elevated serum LCN2 protein level (∼ 6,000 ng/mL) postinfection and more than 60% post-PHx (∼ 700 ng/mL). Interestingly, both Lcn2(Hep-/-) and global Lcn2 knockout (Lcn2(-/-)) mice demonstrated comparable increases in susceptibility to infection with K. pneumoniae or E. coli. These mice also had increased enteric bacterial translocation from the gut to the mesenteric lymph nodes and exhibited reduced liver regeneration after PHx. Treatment with interleukin (IL)-6 stimulated hepatocytes to produce LCN2 in vitro and in vivo. Hepatocyte-specific ablation of the IL-6 receptor or Stat3, a major downstream effector of IL-6, markedly abrogated LCN2 elevation in vivo. Furthermore, chromatin immunoprecipitation (ChIP) assay revealed that STAT3 was recruited to the promoter region of the Lcn2 gene upon STAT3 activation by IL-6. CONCLUSION: Hepatocytes are the major cell type responsible for LCN2 production after bacterial infection or PHx, and this response is dependent on IL-6 activation of the STAT3 signaling pathway. Thus, hepatocyte-derived LCN2 plays an important role in inhibiting bacterial infection and promoting liver regeneration.
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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 | 0.000 |
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".