Inhaled argon dilates pulmonary vasculature in rat isolated lungs
Bibliographic record
Abstract
During cardiopulmonary resuscitation, pulmonary vasoconstriction due to hypoxia and hypercarbia restricts blood flow from the right to the left heart, resulting in reduced cardiac output that further inhibits adequate oxygenation and the ability to distribute oxygenated blood and medications. An inhaled pulmonary vasodilator could attenuate vasoconstriction and, therefore, increase cardiac output. We used rat isolated lungs to test if inhaled Argon leads to pulmonary vasodilation in phenylephrine-treated lungs. Lungs of 13 adult male Sprague–Dawley rats were isolated, ventilated, and perfused. Pulmonary artery and left atrium were cannulated and lungs perfused at constant flow with 4% albumin physiological saline solution. Controls ( n = 6) were ventilated with 65% N2, 5% CO2, 30% O2, and Argon lungs ( n = 7) with 65% Argon, 5% CO2, and 30% O2. Pulmonary mean arterial pressure (pMAP) and airway pressure (AWP) were recorded continuously, and pulmonary vascular resistance (PVR) was calculated. Following baseline readings, phenylephrine, a pulmonary vasoconstrictor, was perfused at increasing concentrations from 10−7 to 10−3 mol/L every 5 min. Statistics: Student’s t test, α = 0.05. Argon led to significantly lower pMAPs and PVRs, independent of AWP. Thus, it significantly dilated pre-constricted pulmonary vessels in an ex vivo lung model. When given during resuscitation, this might aid to increase cardiac output.
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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) | 0.000 | 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 | 0.000 | 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".