TREATING HYPOXIC NEONATAL PIGLETS WITH NG-MONOMETHYL-L-ARGININE AFTER RESUSCITATION WORSENED HEMODYNAMIC RECOVERY DESPITE REDUCING OXIDATIVE STATE
Bibliographic record
Abstract
Background Excessive nitric oxide (NO) generated during hypoxic-reoxygenation may cause injuries to the heart and brain. Beneficial effects of reducing NO generation are unclear, especially in asphyxiated newborns who commonly have pulmonary hypertension following resuscitation. Objectives Using a swine model of acute neonatal asphyxia, we evaluated effects of NG-monomethyl-L-arginine (NMMA, a non-selective NO synthase inhibitor) on systemic, pulmonary and carotid hemodynamic changes after reoxygenation. Methods Anesthetized piglets (1–3 d) were instrumented and block-randomized into a sham-operated group (n = 5) and 3 hypoxia-reoxygenation groups (2 h normocapnic alveolar hypoxia followed by 4 h reoxygenation, n = 7/group). At 5 min after reoxygenation, piglets were given either saline or NMMA (0.1[L] or 1[H] mg/kg/h) in a blinded, randomized fashion. Systemic and pulmonary arterial pressures (SAP, PAP, respectively), pulmonary and carotid arterial blood flows were recorded and myocardial and cerebral glutathione and nitrotyrosine levels were compared. Results Asphyxiated piglets were hypotensive, acidotic and had cardiogenic shock. Post-resuscitation NMMA treatment decreased (1) cardiac output and stroke volume (by 28 and 34% and by 26 and 57% of respective values of saline controls for L and H, respectively); (2) carotid oxygen delivery (by 17 and 52% for L and H, respectively) with corresponding changes in carotid flow and vascular resistance during reoxygenation; and (3) myocardial and cerebral oxidized glutathione and nitrotyrosine levels. With no significant improvement in SAP, NMMA treatment caused pulmonary hypertension with increased PAP and PAP/SAP ratio. Conclusions In newborn piglets with hypoxia-reoxygenation, post-resuscitation inhibition of NO production worsened systemic, pulmonary and carotid hemodynamic recovery, despite of reducing oxidative indices.
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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) | 0.002 | 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".