Mild hypothermia attenuates changes in respiratory system mechanics and modifies cytokine concentration in bronchoalveolar lavage fluid during low lung volume ventilation
Bibliographic record
Abstract
Hypothermia was shown to attenuate ventilator-induced lung injury due to large tidal volumes. It is unclear if the protective effect of hypothermia is maintained under less injurious mechanical ventilation in animals without previous lung injury. Tracheostomized rats were randomly allocated to non-ventilated group (group C) or ventilated groups of normothermia (group N) and mild hypothermia (group H). After two hours of mechanical ventilation with inspiratory fraction of oxygen 1.0, respiratory rate 60 min(-1), tidal volume 10 ml x kg(-1), positive end-expiratory pressure (PEEP) 2 cm H2O or immediately after tracheostomy in non-ventilated animals inspiratory pressures were recorded, rats were sacrificed, pressure-volume (PV) curve of respiratory system constructed, bronchoalveolar lavage (BAL) fluid and aortic blood samples obtained. Group N animals exhibited a higher rise in peak inspiratory pressures in comparison to group H animals. Shift of the PV curve to right, higher total protein and interleukin-6 levels in BAL fluid were observed in normothermia animals in comparison with hypothermia animals and non-ventilated controls. Tumor necrosis factor-alpha was lower in the hypothermia group in comparison with normothermia and non-ventilated groups. Mild hypothermia attenuated changes in respiratory system mechanics and modified cytokine concentration in bronchoalveolar lavage fluid during low lung volume ventilation in animals without previous lung injury.
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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 | 0.000 | 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 | 0.001 |
| 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".