Myeloid liver kinase B1 contributes to lung inflammation induced by lipoteichoic acid but not by viable Streptococcus pneumoniae
Bibliographic record
Abstract
BACKGROUND: Liver kinase B1 (Lkb1, gene name Stk11) functions as a tumor suppressor in cancer. Myeloid cell Lkb1 potentiates lung inflammation induced by the Gram-negative bacterial cell wall component lipopolysaccharide and in host defense during Gram-negative pneumonia. Here, we sought to investigate the role of myeloid Lkb1 in lung inflammation elicited by the Gram-positive bacterial cell wall component lipoteichoic acid (LTA) and during pneumonia caused by the Gram-positive respiratory pathogen Streptococcus pneumoniae (Spneu). METHODS: Alveolar and bone marrow derived macrophages (AMs, BMDMs) harvested from myeloid-specific Lkb1 deficient (Stk11-ΔM) and littermate control mice were stimulated with LTA or Spneu in vitro. Stk11-ΔM and control mice were challenged via the airways with LTA or infected with Spneu in vivo. RESULTS: Lkb1 deficient AMs and BMDMs produced less tumor necrosis factor (TNF)α upon activation by LTA or Spneu. During LTA-induced lung inflammation, Stk11-ΔM mice had reduced numbers of AMs in the lungs, as well as diminished cytokine release and neutrophil recruitment into the airways. During pneumonia induced by either encapsulated or non-encapsulated Spneu, Stk11-ΔM and control mice had comparable bacterial loads and inflammatory responses in the lung, with the exception of lower TNFα levels in Stk11-ΔM mice after infection with the non-encapsulated strain. CONCLUSION: Myeloid Lkb1 contributes to LTA-induced lung inflammation, but is not important for host defense during pneumococcal pneumonia.
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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".