Early nutrition and white matter microstructure in children born very low birth weight
Bibliographic record
Abstract
Abstract Infants born at very low birth weight (<1500 g) are vulnerable to nutritional deficits during their first postnatal month, which are associated with poor neurodevelopmental outcomes. Despite this knowledge, the impact of early postnatal nutrition on white matter microstructure in children born with very low birth weight has not been investigated. In this prospective cohort study, we employed a whole-brain approach to investigate associations between precise estimates of nutrient intake within the first postnatal month with white matter microstructure at 5 years of age. Detailed information about breastmilk, macronutrient and energy intakes during this period were prospectively recorded for all participants. Multi-shell diffusion and T1-weighted MRIs were acquired in 41 children (21 males; mean scan age: 5.75 ± 0.22 years; mean birth weight: 1028.6 ± 256.8 g). The diffusion tensor imaging and neurite orientation dispersion and density imaging models were used to obtain maps of fractional anisotropy, radial diffusivity, orientation dispersion and neurite density indices. Tract-based spatial statistics was used to test associations between metrics of white matter microstructure with breastmilk, macronutrient (protein, lipids and carbohydrate) and energy intake. Associations between white matter microstructure and cognitive outcomes were also examined. Compared to children who did not meet enteral feeding recommendations, those who achieved enteral protein, lipid and energy recommendations during the first postnatal month showed improved white matter maturation at 5 years. Among the macronutrients, greater protein intake contributed most to the beneficial effect of nutrition, showing widespread increases in fractional anisotropy and reductions in radial diffusivity. No significant associations were found between white matter metrics with breastmilk or carbohydrate intake. Voxel-wise analyses with cognitive outcomes revealed significant associations between higher fractional anisotropy and neurite density index with higher processing speed scores. Lower radial diffusivity and orientation dispersion index were also associated with improved processing speed. Our findings support the long-term impacts of early nutrition on white matter microstructure, which in turn is related to cognitive outcomes. These results provide strong support for early postnatal nutritional intervention as a promising strategy to improve long-term cognitive outcomes of infants born at very low birth weight.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".