Influence of gender and interleukin‐10 deficiency on the inflammatory response during lung infection with <i>Pseudomonas aeruginosa</i> in mice
Bibliographic record
Abstract
Cystic fibrosis females have a worse prognosis compared to male patients. Furthermore, cystic fibrosis patients infected with Pseudomonas aeruginosa have been shown to have dysregulated cytokine profiles, as higher levels of tumour necrosis factor alpha (TNF-alpha), interleukin (IL)-8, and lower levels of IL-10 are found in the bronchoalveolar lavage fluid compared to healthy controls. The present study was aimed at investigating the importance of gender and IL-10 in the susceptibility of C57BL/6 mice to pulmonary infection with Pseudomonas aeruginosa. We found that wildtype females were more susceptible than males to infection, as we observed greater weight loss, higher bacterial load, and inflammatory mediators in their lungs. IL-10 knockout mice, both females and males, had higher levels of TNF-alpha in the lungs compared to wildtype mice and maintained higher levels of polymorphonuclear cells and lower levels of macrophages for a longer period of time. Our results demonstrate that the number of bacteria recovered from the lungs of IL-10 knockout male mice was significantly higher than that observed in their wildtype male counterparts and we show that neutralization of IL-10 in infected female mice for a prolonged period of time leads to increased susceptibility to infection. Results reported in this study clearly demonstrate that females, both wildtype and IL-10 knockout mice are more susceptible to Pseudomonas aeruginosa infection than males, and that they mount a stronger inflammatory response in the lungs.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".