Striatal development involves a switch in gene expression networks, followed by a myelination event: implications for neuropsychiatric disease
Bibliographic record
Abstract
Abnormal development of striatal neurons is thought to be part of the pathology underlying psychiatric illness. We studied striatal gene expression patterns during an active striatal maturation period, the first two postnatal weeks in the rat. This parallels human striatal development during the second trimester, when prenatal stress is thought to lead to increased risk for neuropsychiatric disorders. Using subtractive hybridization and quantitative real‐time PCR, we characterize the developmental expression of more than 60 genes, many not previously known to play a role in neuromaturation. We show that during the first two postnatal weeks in the rat, an early gene expression network that lacks key striatal‐specific signaling pathways is downregulated and replaced by a mature gene expression network, containing key striatal‐specific genes, which confer functional identity to these neurons. Hence, early postnatal striatal neurons lack many of their key characteristics. This maturation process is followed by a rise in the expression of myelination genes, indicating a striatal‐specific myelination event. This strictly controlled developmental program is likely to be susceptible to disruption by external factors. Alterations in its normal progression may play a role in the etiology of neuropsychiatric disease. 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".