Angiogenesis-associated pathways play critical roles in neonatal sepsis outcomes
Bibliographic record
Abstract
Neonatal sepsis is a major cause of childhood mortality. Limited diagnostic tools and mechanistic insights have hampered our abilities to develop prophylactic or therapeutic interventions. Biomarkers in human neonatal sepsis have been repeatedly identified as associated with dysregulation of angiopoietin signaling and altered arachidonic acid metabolism. We here provide the mechanistic evidence in support of the relevance for these observations. Angiopoetin-1 (Ang-1), which promotes vascular integrity, was decreased in blood plasma of human and murine septic newborns. In preclinical models, administration of Ang-1 provided prophylactic protection from septic death. Arachidonic acid metabolism appears to be functionally connected to Ang-1 via reactive oxygen species (ROS) with a direct role of nitric oxide (NO). Strengthening this intersection via oral administration of arachidonic acid and/or the NO donor L-arginine provided prophylactic as well as therapeutic protection from septic death while also increasing plasma Ang-1 levels among septic newborns. Our data highlight that targeting angiogenesis-associated pathways with interventions that increase Ang-1 activity directly or indirectly through ROS/eNOS provide promising avenues to prevent and/or treat severe neonatal sepsis.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".