Children Born to Women Treated for Hypothyroidism During Pregnancy Show Abnormal Corpus Callosum Development
Bibliographic record
Abstract
BACKGROUND: Thyroid hormone (TH) is essential for the developing brain, and because the fetal thyroid develops relatively late in gestation, the maternal TH supply is critical for fetal brain development. However, if the mother has hypothyroidism during pregnancy, fetal brain and neuropsychological development may be compromised. Rodents experiencing maternal TH insufficiency show abnormal corpus callosum (CC) morphology, but it is not known if children born to women treated for hypothyroidism (HYPO) show similar effects. The purpose of the current study was to investigate HYPO for CC morphology and morphometry and to determine whether any specific CC abnormalities were associated aspects of maternal hypothyroidism and were correlated with reduced neuropsychological functioning in the children. METHODS: ANALYZE software was used to trace CCs in archived magnetic resonance imaging scans from 22 HYPO and 22 matched controls. Areas of two sub-regions and six segments and different shape metrics (angles, lengths, ratios) were determined. CC parameters were correlated with maternal thyrotropin (TSH) values and number of hypothyroid trimesters as well as the child's neuropsychological test performance. RESULTS: HYPO showed a smaller anterior CC and genu and larger posterior CC and splenium areas than controls as well as shape abnormalities in genu and splenium. Results were correlated with the duration of maternal hypothyroidism. Executive function skills were positively associated with genu size in HYPO, while verbal comprehension skills were negatively associated with splenium and overall posterior CC sizes. CONCLUSIONS: Maternal hypothyroidism contributes to CC abnormalities in the offspring, and effects differ for anterior versus posterior CC regions.
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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".