Effect of ventilation strategy and surfactant on inflammation in experimental pneumonia
Bibliographic record
Abstract
This study explored, the inflammatory response during experimental pneumonia in surfactant-depleted animals as a function of ventilation strategies and surfactant treatment. Following intratracheal instillation of Group B streptococci (GBS), surfactant-depleted piglets were treated with conventional (positive-end expiratory pressure (PEEP) of 5 cmH2O, tidal volume 7 mL x kg(-1)) or open lung ventilation. During the latter, collapsed alveoli were recruited by applying high peak inspiratory pressures for a short period of time, combined with high levels of PEEP and the smallest possible pressure amplitude. Subgroups in both ventilation arms also received exogenous surfactant. Conventionally ventilated healthy animals receiving GBS and surfactant-depleted animals receiving saline served as controls. In contrast with both control groups, surfactant-depleted animals challenged with GBS and conventional ventilation showed high levels of interleukin (IL)-8, tumour necrosis factor (TNF)-alpha and myeloperoxidase in bronchoalveolar lavage fluid after 5 h of ventilation. Open lung ventilation attenuated this inflammatory response, but exogenous surfactant did not. Systemic dissemination of the inflammatory response was minimal, as indicated by low serum levels of IL-8 and TNF-alpha. In conclusion, the current study indicates that the ventilation strategy, but not exogenous surfactant, is an important modulator of the inflammation during Group B streptococci pneumonia in mechanically ventilated surfactant-depleted animals.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".