The potential role for arachidonic and docosahexaenoic acids in protection against some central nervous system injuries in preterm infants
Bibliographic record
Abstract
The risk of central nervous, visual, and auditory damage increases from 2/1000 live births in the normal birthweight to > 200/1000 as birthweight falls below 1500 g. Such babies are most likely to be born preterm. Advances in infant care have led to increasing numbers of very-low-birthweight, preterm infants surviving to school age with moderate to severe brain damage. Steroids are one of the current treatments, but they cause significant, long-term problems. The evidence reported here suggests an additional approach to protecting the very preterm infant by supporting neurovascular membrane integrity. The complications of preterm, very-low-birthweight babies include bronchopulmonary dysplasia, retinopathy of prematurity, intraventricular hemorrhage, periventricular leukomalacia, and necrotizing enterocolitis, all of which have a vascular component. Arachidonic acid (AA) and DHA are essential, structural, and functional constituents of cell membranes. They are especially required for the growth and function of the brain and vascular systems, which are the primary biofocus of human fetal growth. Molecular dynamics and experimental evidence suggest that DHA could be the ligand for the retinoid X receptor (RXR) in neural tissue. RXR activation is an obligatory step in signaling to the nucleus and in the regulation of gene expression. Very preterm babies are born with minimal fat stores and suboptimal circulating levels of these nutrients. Postnatally, they lose the biomagnification of the proportions of AA and DHA by the placenta for the fetus. No current nutritional management repairs these deficits. The placental biomagnification profile highlights AA rather than DHA. The resultant fetal FA profile closely resembles that of the vascular endothelium and not the brain. Without this nourishment, cell membrane abnormalities would be predicted. We present a scientific rationale for a common pathogenic process in the complications of prematurity.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".