L-Citrulline in Neonates: From Bench to Bed Side
Bibliographic record
Abstract
L-citrulline (L-CIT), a precursor to L-arginine (L-ARG), is a key contributor to the nitric oxide (NO) signaling pathway. Endothelial dysfunction, characterized by deficient nitric oxide synthesis, is implicated in the pathogenesis of various neonatal conditions such as necrotizing enterocolitis (NEC) and bronchopulmonary dysplasia (BPD) associated pulmonary hypertension (PH). This review summarizes the current evidence around the possible role of L-CIT supplementation in the treatment of these conditions. Detoxification of endogenously produced superoxide radicals is inadequate in preterm infants due to immature antioxidants that leads to the production of peroxynitrite, a reactive oxygen-free radical that is cytotoxic and causes damage to organelles and cellular membranes, further disrupting the coupling of endothelial NO synthase enzyme and the generation of high levels of reactive nitrogen and oxygen species. Animal studies in lipopolysaccharide-induced models of chorioamnionitis and hyperoxia- and inflammation-induced BPD-PH in rodent lung models revealed that L-CIT supplementation significantly mitigated structural changes in the pulmonary vasculature, preserved alveolar growth, and increased vascular endothelial growth factor gene expression, highlighting the anti-inflammatory and antioxidant effects of L-CIT supplementation. Similar benefits were noted in newborn piglet models of chronic hypoxia-induced PH and NEC. Pharmacokinetic studies in neonates have shown doses of 100-300 mg/kg/day to be safe and well tolerated. A few studies have shown the beneficial effects of L-CIT supplementation in pulmonary hypertension secondary to congenital heart disease, but evidence of efficacy in the neonatal population is lacking. While L-CIT shows promise in the treatment of various neonatal conditions, adequately powered studies to evaluate the safety and efficacy of L-CIT supplementation post-surgical NEC and BPD ± PH in the extremely preterm population are needed to translate this novel therapy to clinical practice.
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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 | 0.001 | 0.001 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".