Therapeutic hypothermia attenuates physiologic, histologic, and metabolomic markers of injury in a porcine model of acute respiratory distress syndrome
Bibliographic record
Abstract
Abstract Acute respiratory distress syndrome (ARDS) is a lung injury characterized by noncardiogenic pulmonary edema and hypoxic respiratory failure. The purpose of this study was to investigate the effects of therapeutic hypothermia on short‐term experimental ARDS. Twenty adult female Yorkshire pigs were divided into four groups ( n = 5 each): normothermic control (C), normothermic injured (I), hypothermic control (HC), and hypothermic injured (HI). Acute respiratory distress syndrome was induced experimentally via intrapulmonary injection of oleic acid. Target core temperature was achieved in the HI group within 1 h of injury induction. Cardiorespiratory, histologic, cytokine, and metabolomic data were collected on all animals prior to and following injury/sham. All data were collected for approximately 12 h from the beginning of the study until euthanasia. Therapeutic hypothermia reduced injury in the HI compared to the I group (histological injury score = 0.51 ± 0.18 vs. 0.76 ± 0.06; p = 0.02) with no change in gas exchange. All groups expressed distinct phenotypes, with a reduction in pro‐inflammatory metabolites, an increase in anti‐inflammatory metabolites, and a reduction in inflammatory cytokines observed in the HI group compared to the I group. Changes to respiratory system mechanics in the injured groups were due to increases in lung elastance (E) and resistance (R) (ΔE from pre‐injury = 46 ± 14 cmH 2 O L −1 , p < 0.0001; ΔR from pre‐injury: 3 ± 2 cmH 2 O L −1 s − , p = 0.30) rather than changes to the chest wall (ΔE from pre‐injury: 0.7 ± 1.6 cmH 2 O L −1 , p = 0.99; ΔR from pre‐injury: 0.6 ± 0.1 cmH 2 O L −1 s − , p = 0.01). Both control groups had no change in respiratory mechanics. In conclusion, therapeutic hypothermia can reduce markers of injury and inflammation associated with experimentally induced short‐term ARDS.
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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".