PGD2 and its derivatives protect against pulmonary bacterial infection in obese mice 2273
Bibliographic record
Abstract
Abstract Description Obesity is a comorbidity for viral infections in the lungs, but the impact of obesity on bacterial lung infections is poorly understood. Utilizing a diet-induced obesity (DIO) mouse model, we previously found that obese mice were more resistant to infection with the virulent bacterium Francisella tularensis (Ft) SchuS4, and an early COX-derived prostaglandins (PG) production, correlated with increased survival. However, we did not determine if this outcome was specific to Ft and if a specific PG mediated the protective response. In this study, DIO and regular weight (RW) mice were intranasally challenged with Ft SchuS4, attenuated Ft LVS, and Bordetella pertussis (Bp). Regardless of the infecting agent, DIO mice were more resistant to infection, had elevated levels of PG and improved inflammatory responses in the lung compared to RW mice. Improved control of inflammation in DIO lungs after infection was associated with decreased cell death and changes in efferocytosis among DIO mice compared to RW mice. We then identified the PG responsible for the protective effects observed in DIO mice. In contrast to PGE2, PGD2 and its metabolites, dampened inflammatory responses following infection of macrophages with Ft or Bp. However, the mechanism of this protection was dependent on the infecting bacterium. Together these data demonstrate that an early production of PGD2 in obesity has important contributions to the relative susceptibility of the host to pulmonary bacterial infection. Funding Sources Supported by the Intramural Research Program of the National Institute of Allergy and Infectious Diseases, National Institutes of Health. Topic Categories Microbial, Parasitic, and Fungal Immunology (MPF)
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.003 | 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".