Region‐specific regulation of 5‐HT1A receptor expression by Pet‐1‐dependent mechanisms<i>in vivo</i>
Bibliographic record
Abstract
Serotonin (5-hydroxytryptamine, 5-HT) neurotransmission is negatively regulated by 5-HT1A autoreceptors on raphe neurons, and is implicated in mood disorders. Pet-1/FEV is an ETS transcription factor expressed exclusively in serotonergic neurons and is essential for serotonergic differentiation, although its regulation of 5-HT receptors has not yet been studied. Here, we show by electrophoretic mobility shift assay that recombinant human Pet-1/FEV binds directly to multiple Pet-1 elements of the human 5-HT1A receptor promoter to enhance its transcriptional activity. In luciferase reporter assays, mutational analysis indicated that while several sites contribute, the Pet-1 site at -1406 bp had the greatest effect on 5-HT1A promoter activity. To address the effect of Pet-1 on 5-HT1A receptor regulation in vivo, we compared the expression of 5-HT1A receptor RNA and protein in Pet-1 null and wild-type littermate mice. In the raphe nuclei of Pet-1-/- mice tryptophan hydroxylase 2 (TPH2) RNA, and 5-HT and TPH immunostaining were greatly reduced, indicating a deficit in 5-HT production. Raphe 5-HT1A RNA and protein levels were also reduced in Pet-1-deficient mice, consistent with an absence of Pet-1-mediated transcriptional enhancement of 5-HT1A autoreceptors in serotonergic neurons. Interestingly, 5-HT1A receptor expression was up-regulated in the hippocampus, but down-regulated in the striatum and cortex. These data indicate that, in addition to transcriptional regulation by Pet-1 in raphe neurons, 5-HT1A receptor expression is regulated indirectly by alterations in 5-HT neurotransmission in a region-specific manner that together may contribute to the aggressive/anxiety phenotype observed in Pet-1 null mice.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".