Sodium nitrite augments lung<i>S</i>-nitrosylation and reverses chronic hypoxic pulmonary hypertension in juvenile rats
Bibliographic record
Abstract
Deficient nitric oxide (NO) signaling plays a critical role in the pathogenesis of chronic neonatal pulmonary hypertension (PHT). Physiological NO signaling is regulated by S-nitrosothiols (SNOs), which act both as a reservoir for NO and as a reversible modulator of protein function. We have previously reported that therapy with inhaled NO (iNO) increased peroxynitrite-mediated nitration in the juvenile rat lung, although having minimal reversing effects on vascular remodeling. We hypothesized that sodium nitrite (NaNO2) would be superior to iNO in enhancing lung SNOs, thereby contributing to reversal of chronic hypoxic PHT. Rat pups were exposed to air or hypoxia (13% O2) from postnatal days 1 to 21. Dose-response prevention studies were conducted from days 1–21 to determine the optimal dose of NaNO2. Animals then received rescue therapy with daily subcutaneous NaNO2(20 mg/kg), vehicle, or were continuously exposed to iNO (20 ppm) from days 14–21. Chronic PHT secondary to hypoxia was both prevented and reversed by treatment with NaNO2. Rescue NaNO2increased lung NO and SNO contents to a greater extent than iNO, without causing nitration. Seven lung SNO proteins upregulated by treatment with NaNO2were identified by multiplex tandem mass tag spectrometry, one of which was leukotriene A4 hydrolase (LTA4H). Rescue therapy with a LTA4H inhibitor, SC57461A (10 mg·kg−1·day−1sc), partially reversed chronic hypoxic PHT. We conclude that NaNO2was superior to iNO in increasing tissue NO and SNO generation and reversing chronic PHT, in part via upregulated SNO-LTA4H.
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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 | 0.000 | 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".