Abstract 4552: Abnormal Cerebrovascular Development in Hypoplastic Left Heart Syndrome During Fetal Life
Bibliographic record
Abstract
Background: Microcephaly is common in newborns with hypoplastic left heart syndrome (HLHS) possibly related to altered cerebral blood flow during fetal life and may lead to neurocognitive deficits. We assessed cerebrovascular growth in fetuses with HLHS. Methods: 27 mid-trimester fetuses with autopsy-confirmed HLHS (gestational age, 23±3 weeks; 11 males) without known chromosomal malformations (2002– 07) were included. Body weight (BW) and head circumference (HC) z scores were calculated. Fetal brain sections were studied in 6 HLHS and 5 normal controls. Brain capillary density (von Willebrand factor, vWf), vascular endothelial growth factor (VEGF), and CD133 (stem cell marker) was measured in germinal matrix, intermediate, subcortical and cortical layers. Results: Mean BW z score was −0.1±1; HC z score was −0.6±1.4. Capillary density (/hpf) was lower in HLHS vs controls in the germinal matrix (4.1±1.4 vs 7.8 ±1.7; p=0.002) (Fig 1 ) and cortex (0.9±0.7 vs 3.5±3.2, p=0.09). Capillaries were larger in the HLHS vs controls (vessel area: 0.059±0.019 vs 0.042±0.016 mm 2 , p=0.005) suggesting reactive dilation to maintain cerebral blood flow. Although VEGF expression was not different between HLHS and controls, the stem cell marker, CD133, was reduced in HLHS (Fig 1 ). Conclusion: This study demonstrates early onset cerebral growth impairment in fetuses with HLHS. This may be related to reduced stem cells and reduced brain capillary density. Whether antenatal interventions that augment antegrade aortic blood flow can improve vascular development and cerebral growth requires further investigation. Figure 1: Brain capillary density (vWF) and CD133 staining was lower in HLHS.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".