Effects of Post-Resuscitation Treatment with N-acetylcysteine on Cardiac Recovery in Hypoxic Newborn Piglets
Bibliographic record
Abstract
AIMS: Although N-acetylcysteine (NAC) can decrease reactive oxygen species and improve myocardial recovery after ischemia/hypoxia in various acute animal models, little is known regarding its long-term effect in neonatal subjects. We investigated whether NAC provides prolonged protective effect on hemodynamics and oxidative stress using a surviving swine model of neonatal asphyxia. METHODS AND RESULTS: Newborn piglets were anesthetized and acutely instrumented for measurement of systemic hemodynamics and oxygen transport. Animals were block-randomized into a sham-operated group (without hypoxia-reoxygenation [H-R, n = 6]) and two H-R groups (2 h normocapnic alveolar hypoxia followed by 48 h reoxygenation, n = 8/group). All piglets were acidotic and in cardiogenic shock after hypoxia. At 5 min after reoxygenation, piglets were given either saline or NAC (intravenous 150 mg/kg bolus + 20 mg/kg/h infusion) via for 24 h in a blinded, randomized fashion. Both cardiac index and stroke volume of H-R controls remained lower than the pre-hypoxic values throughout recovery. Treating the piglets with NAC significantly improved cardiac index, stroke volume and systemic oxygen delivery to levels not different from those of sham-operated piglets. Accompanied with the hemodynamic improvement, NAC-treated piglets had significantly lower plasma cardiac troponin-I, myocardial lipid hydroperoxides, activated caspase-3 and lactate levels (vs. H-R controls). The change in cardiac index after H-R correlated with myocardial lipid hydroperoxides, caspase-3 and lactate levels (all p<0.05). CONCLUSIONS: Post-resuscitation administration of NAC reduces myocardial oxidative stress and caused a prolonged improvement in cardiac function and in newborn piglets with H-R insults.
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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 | 0.000 |
| 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".