Clinical Isolates of <i>Pseudomonas aeruginosa</i> from Chronically Infected Cystic Fibrosis Patients Fail To Activate the Inflammasome during Both Stable Infection and Pulmonary Exacerbation
Bibliographic record
Abstract
Immune recognition of pathogen-associated ligands leads to assembly and activation of inflammasomes, resulting in the secretion of inflammatory cytokines IL-1β and IL-18 and an inflammatory cell death called pyroptosis. Inflammasomes are important for protection against many pathogens, but their role during chronic infectious disease is poorly understood. Pseudomonas aeruginosa is an opportunistic pathogen that persists in the lungs of cystic fibrosis (CF) patients and may be responsible for the repeated episodes of pulmonary exacerbation characteristic of CF. P. aeruginosa is capable of inducing potent inflammasome activation during acute infection. We hypothesized that to persist within the host during chronic infection, P. aeruginosa must evade inflammasome activation, and pulmonary exacerbations may be the result of restoration of inflammasome activation. We therefore isolated P. aeruginosa from chronically infected CF patients during stable infection and exacerbation and evaluated the impact of these isolates on inflammasome activation in macrophages and neutrophils. P. aeruginosa isolates from CF patients failed to induce inflammasome activation, as measured by the secretion of IL-1β and IL-18 and by pyroptotic cell death, during both stable infection and exacerbation. Inflammasome evasion likely was due to reduced expression of inflammasome ligands and reduced motility and was not observed in environmental isolates or isolates from acute, non-CF infection. These results reveal a novel mechanism of pathogen adaptation by P. aeruginosa to avoid detection by inflammasomes in CF patients and indicate that P. aeruginosa-activated inflammasomes are not involved in CF pulmonary exacerbations.
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 | 0.001 |
| 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 | 0.001 | 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".