Inflammasome Activation by ATP Enhances Citrobacter rodentium Clearance through ROS Generation
Bibliographic record
Abstract
BACKGROUND: Nod-like receptor family, pyrin domain containing 3 (NLRP3) is an important cytosolic sensor of cellular stress and infection. Once activated, NLRP3 forms a multiprotein complex (inflammasome) that triggers the maturation and secretion of interleukin (IL)-1β and IL-18. We aimed to define the consequences of NLRP3 induction, utilizing exogenous adenosine triphosphate (ATP) as an inflammasome activator, to determine if inflammasome activation increases macrophage killing of Citrobacter rodentium and define mechanisms. METHODS: Bacterial survival was measured using a gentamicin protection assay. Inflammasome activation or inhibition in mouse J774A.1 macrophages were assessed by measuring IL-1β; cytokines and reactive oxygen species (ROS) were measured by ELISA and DCFDA, respectively. RESULTS: Activation of the inflammasome increased bacterial killing by macrophages and its inhibition attenuated this effect with no impact on phagocytosis or cell death. Furthermore, inflammasome activation suppressed pro-inflammatory cytokines during infection, possibly due to more effective bacterial killing. While the infection increased ROS production, this effect was reduced by inflammasome inhibitors, indicating that ROS is inflammasome-dependent. ROS inhibitors increased bacterial survival in the presence of ATP, suggesting that inflammasome-induced bacterial killing is mediated, at least in part, by ROS activity. CONCLUSION: Improving inflammasome activity during infection may increase bacterial clearance by macrophages and reduce subsequent microbe-induced inflammation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".