Thyroid hormones regulate reelin expression in neuropsychiatric disorders
Bibliographic record
Abstract
The incidence and prevalence of hypothyroidism in pregnancy have increased over the past two decades, leading to the occurrence of neuropsychiatric disorders. However, the underlying mechanisms of thyroid hormone (TH)-regulated gene expression and neuropsychiatric development during the postnatal period remain unknown. Recent achievements have shown that reelin, a large extracellular glycoprotein, plays a crucial role in neuronal migration and localization during the development of neocortex and cerebellar cortex, thereby participating in the development of neuropsychiatric diseases. Reelin-induced neuronal migration requires triiodothyronine (T3) from the deiodination of thyroxine (T4) by fetal brain deiodinases. Previous studies have reported decreased reelin levels and abnormal gene expression, which are the same as the pathological alternations in reelin-induced neuropsychiatric disorders including schizophrenia and autism. Low T3 in the fetal brain due to hypothyroxinemia during pregnancy may be detrimental to neuronal migration, leading to neuropsychiatric disorders. In this review, we focus on the reelin expression between hypothyroidism and neuropsychiatric disorders.
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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) | 0.001 | 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".