Striatal development involves a switch in gene expression networks, followed by a myelination event: Implications for neuropsychiatric disease
Bibliographic record
Abstract
Because abnormal development of striatal neurons is thought to be the part of pathology underlying major psychiatric illnesses, we studied the expression pattern of genes involved in striatal development and of genes comprising key striatal-specific pathways, during an active striatal maturation period, the first two postnatal weeks in rat. This period parallels human striatal development during the second trimester, when prenatal stress is though to lead to increased risk for neuropsychiatric disorders. To identify genes involved in this developmental process, we used subtractive hybridization, followed by quantitative real-time PCR, which allowed us to characterize the developmental expression of over 60 genes, many not previously known to play a role in neuromaturation. Of these 12 were novel transcripts, which did not match known genes, but which showed strict developmental expression and may play a role in striatal neurodevelopment. An additional 89 genes were identified as strong candidates for involvement in this neurodevelopmental process. We show that during the first two postnatal weeks in rat, an early gene expression network, still lacking key striatal-specific signaling pathways, is downregulated and replaced by a mature gene expression network, containing key striatal-specific genes including the dopamine D1 and D2 receptors, conferring to these neurons their functional identity. Therefore, before this developmental switch, striatal neurons lack many of their key phenotypic characteristics. This maturation process is followed by a striking rise in expression of myelination genes, indicating a striatal-specific myelination event. Such strictly controlled developmental program has the potential to be a point of susceptibility to disruption by external factors. Indeed, this period is known to be a susceptibility period in both humans and rats.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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".