Omega-3 polyunsaturated fatty acids improve host response in chronic<i>Pseudomonas aeruginosa</i>lung infection in mice
Bibliographic record
Abstract
Pseudomonas aeruginosa is a gram-negative bacilli frequently encountered in human pathology. This pathogen is involved in a large number of nosocomial infections and chronic diseases. Herein we investigated the effects of polyunsaturated fatty acids (PUFA) in chronic Pseudomonas aeruginosa lung infection. C57BL/6 mice were fed for 5 wk with specifically designed diets with high contents in either omega-3 (omega-3) or omega-6 PUFA and compared to a control diet. P. aeruginosa included in agarose beads was then instilled intratracheally, and the animals were studied for 7 days. On the 4th day, the mice fed with the omega-3 diet had a higher lean body mass gain and a lower omega-6:omega-3 ratio of fatty acids extracted from the lung tissue compared with the other groups (P < 0.05). The omega-3 group had the lowest mortality. Distal alveolar fluid clearance (DAFC) as well as the inflammatory response and the cellular recruitment were higher in the omega-3 group on the 4th day. The effect on DAFC was independent of alpha-epithelial Na(+) channels (alpha-ENaC), beta-ENaC, and alpha(1)-Na-K-ATPase mRNA expressions, which were not altered by the different diets. In conclusion, a diet enriched in omega-3 PUFA can change lung membrane composition and improve survival in chronic pneumonia. This effect on survival is probably multifactorial involving the increased DAFC capacity as well as the optimization of the initial inflammatory response. This work suggests that a better control of the omega-6/omega-3 PUFA balance may represent an interesting target in the prevention and/or control of P. aeruginosa infection in patients.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".