Using omics to breathe new life into our understanding of the ductus arteriosus oxygen response
Bibliographic record
Abstract
The ductus arteriosus (DA) connects the aorta to the pulmonary artery (PA), directing placentally oxygenated blood away from the developing lungs. High pulmonary vascular resistance and low systemic vascular resistance facilitate shunting of blood in utero from the pulmonary to the systemic circulation through the widely patent DA, thereby optimizing fetal oxygen (O2) delivery. With the transition from fetal (hypoxia) to neonatal (normoxia) oxygen conditions, the DA constricts while the PA dilates. This process often fails in prematurity, promoting congenital heart disease. Impaired O2-responsivness in the DA promotes persistent ductus arteriosus (PDA), the most common form of congenital heart disease. Knowledge of DA oxygen sensing has greatly advanced in the past few decades, however we still lack a complete understanding of the sensing mechanism. The genomic revolution of the past two decades has facilitated unprecedented discovery in every biological system. This review will demonstrate how multiomic integration of data generated from the DA can breathe new life into our understanding of the DA's oxygen response.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".