Therapeutic Hypercapnia Reduces Pulmonary and Systemic Injury following <i>In Vivo</i> Lung Reperfusion
Bibliographic record
Abstract
Permissive hypercapnia, involving tolerance to elevated Pa(CO(2)), is associated with reduced acute lung injury (ALI), thought to result from reduced mechanical stretch, and improved outcome in ARDS. However, deliberately elevating inspired CO(2) concentration alone (therapeutic hypercapnia, TH) protects against ALI in ex vivo models. We investigated whether TH would protect against ALI in an in vivo model of lung ischemia-reperfusion (IR). Anesthetized open chest rabbits were ventilated (standard eucapnic settings), and were randomized to TH (FI(CO(2)) 0.12) versus control (FI(CO(2)) 0.00). Pa(CO(2)) and arterial pH values achieved in the TH versus CON groups were 101 +/- 3 versus 44.4 +/- 4 mm Hg and 7.10 +/- 0.03 versus 7.37 +/- 0.03, respectively. Following left lung ischemia and reperfusion, TH versus control was associated with preservation of lung mechanics, attenuation of protein leakage, reduction in pulmonary edema, and improved oxygenation. Indices of systemic protection included improved acid-base and lactate profile, in the absence of systemic hypoxemia. In the TH group, mean BALF TNF-alpha levels were 3.5% of CON levels (p < 0.01), and mean 8-isoprostane levels were 30% of CON levels (p = 0.02). Western blot analysis demonstrated reduced lung tissue nitrotyrosine in TH, indicating attenuation of tissue nitration. Finally, preliminary data suggest that TH may attenuate apoptosis following lung IR. We conclude that in the current model TH is protective versus IR lung injury and mechanisms of protection include preservation of lung mechanics, attenuation of pulmonary inflammation, and reduction of free radical mediated injury. If these findings are confirmed in additional models, TH may become a candidate for clinical testing in critical care.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".