Muramyldipeptide Modulates CXCL‐8 Release of BEAS‐2B Cells via NOD2
Bibliographic record
Abstract
Chronic inflammation and acute exacerbations are pathophysiological features of chronic obstructive pulmonary disease (COPD). An impaired immune response to bacterial pathogens can contribute to both of them. Nucleotide oligomerization domain 2 (NOD2) is an intracellular receptor of innate immunity for muramyldipeptide (MDP). Mutations of the NOD2 gene followed by decreased recognition of MDP are associated with chronic intestinal inflammation and pulmonary complications of patients with allogenic stem cell transplant and sepsis. Our study provides evidence that NOD2, toll-like receptor 4 (TLR4) and the adapter protein receptor-interacting protein 2 (RIP2) are induced by tumor-necrosis factor-alpha (TNF-alpha) and interferon-gamma (IFN-gamma) in the bronchial epithelial cell line BEAS-2B. We also demonstrate that lipopolysaccharide (LPS) can further increase NOD2 transcription in a TNF-alpha and IFN-gamma-induced activation state. In addition, we show that, while MDP fails to enhance CXCL-8 release from otherwise unstimulated BEAS-2B cells, a 12 h prestimulation period with TNF-alpha and IFN-gamma primes the cells for an additional increase of CXCL-8 secretion via induction of NOD2 and RIP2. LPS itself significantly augments CXCL-8 production and co-administration of MDP further increases cytokine secretion. Finally, overexpression of an SNP13 mutant decreased MDP-induced chemokine production in BEAS-2B cells compared with NOD2 wild type overexpression. Taken together, our work indicates that MDP and NOD2 play an important role for CXCL-8 release of BEAS-2B cells following LPS-challenge via synergistic interactions between MDP and LPS.
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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) | 0.000 | 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) | 0.001 | 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".