Alterations in frontostriatal pathways in children born very preterm
Bibliographic record
Abstract
AIM: Children born very preterm (<32wks' gestation) are at risk of white matter injury, particularly in frontostriatal pathways that mediate executive functioning. However, it is unclear whether very preterm children without evidence of neonatal brain injury manifest long-term white matter microstructural differences once they reach school age and if this is related to cognitive impairments. METHOD: Twenty school-aged children born very preterm (11 males, nine females; mean age 8y 6mo, standard error [SE] 1.68mo, range 7y 7mo-9y 6mo; gestational age range 24-30wks, mean gestational age 26.9wks, SE 0.4wk; birthweight 988 g, SE 46 g, range 570-1424 g) without evidence of neonatal brain injury, and 20 sex- and age-matched term-born children (mean age 8y 4.8mo, SE 1.92mo; range 7y 2mo-9y-10.8mo) underwent neurodevelopmental assessment and diffusion tensor imaging. RESULTS: Fractional anisotropy, mean diffusivity, axial diffusivity, and radial diffusivity were calculated within all white matter pathways and within frontostriatal projections. Children born preterm had decreased fractional anisotropy in the territories of the left external capsule, superior longitudinal fasciculus, uncinate fasciculus, and inferior fronto-occipital fasciculus. Measures of intelligence were negatively correlated with frontostriatal fractional anisotropy only in males born preterm. INTERPRETATION: Results indicate that very preterm-born children exhibit white matter disturbances that persist into middle childhood, with potential sex differences in the association between these white matter alterations and cognitive function.
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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 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 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".