The Pseudomonas aeruginosa Autoinducer 3O-C12 Homoserine Lactone Provokes Hyperinflammatory Responses from Cystic Fibrosis Airway Epithelial Cells
Bibliographic record
Abstract
The discovery of novel antiinflammatory targets to treat inflammation in the cystic fibrosis (CF) lung stands to benefit patient populations suffering with this disease. The Pseudomonas aeruginosa quorum sensing autoinducer N-3-oxododecanoyl homoserine lactone (3O-C12) is an important bacterial virulence factor that has been reported to induce proinflammatory cytokine production from a variety of cell types. The goal of this study was to examine the ability of 3O-C12 to induce proinflammatory cytokine production in normal and CF bronchial epithelial cells, and better understand the cellular mechanisms by which this cytokine induction occurs. 3O-C12 was found to induce higher levels of IL-6 production in the CF cell lines IB3-1 and CuFi, compared to their corresponding control cell lines C38 and NuLi. Systems biology and network analysis revealed a high predominance of over-represented innate immune pathways bridged together by calcium-dependant transcription factors governing the transcriptional responses of A549 airway cells to stimulation with 3O-C12. Using calcium-flux assays, 3O-C12 was found to induce larger and more sustained increases in intracellular calcium in IB3-1 cells compared to C38, and blocking this calcium flux with BAPTA-AM reduced the production of IL-6 by IB3-1 to the levels produced by C38. These data suggest that 3O-C12 induces proinflammatory cytokine production in airway epithelial cells in a calcium-dependent manner, and that dysregulated calcium storage or signalling in CF cells results in an increased production of proinflammatory cytokines.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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 | 0.000 |
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".