Inflammasome-Mediated IL-1β Production in Humans with Cystic Fibrosis
Bibliographic record
Abstract
BACKGROUND: Inflammation and infection are major determinants of disease severity and consequently, the quality of life and outcome for patients with cystic fibrosis (CF). Interleukin-1 beta (IL-1β) is a key inflammatory mediator. Secretion of biologically active IL-1β involves inflammasome-mediated processing. Little is known about the contribution of IL-1β and the inflammasomes in CF inflammatory disease. This study examines inflammasome-mediated IL-1β production in CF bronchial epithelial cell lines and human patients with CF. RESULTS: Bronchial epithelial cell lines were found to produce negligible amounts of basal or stimulated IL-1β compared to hematopoeitic cells and they did not significantly upregulate caspase-1 activity upon inflammasome stimulation. In contrast, peripheral blood mononuclear cells (PBMCs) from both CF and healthy control subjects produced large amounts of IL-1β and strongly upregulated caspase-1 activity upon inflammasome stimulation. PBMCs from CF patients and controls displayed similar levels of caspase-1 activation and IL-1β production when stimulated with inflammasome activators. This IL-1β production was dependent on NF-κB activity and could be enhanced by priming with LPS. Finally, chemical inhibition of CFTR activity in control PBMCs and THP-1 cells did not significantly alter IL-1β or IL-8 production in response to P. aeruginosa. CONCLUSION: Hematopoeitic cells appear to be the predominant source of inflammasome-induced pro-inflammatory IL-1β in CF. PBMCs derived from CF subjects display preserved inflammasome activation and IL-1β secretion in response to the major CF pathogen Pseudomonas aeruginosa. However, our data do not support the hypothesis that increased IL-1β production in CF subjects is due to an intrinsic increase in NF-κB activity through loss of CFTR function.
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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 | 0.001 |
| 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 | 0.000 |
| 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".