Transcriptional dysregulation of 5-HT1A autoreceptors in mental illness
Bibliographic record
Abstract
The serotonin-1A (5-HT1A) receptor is among the most abundant and widely distributed 5-HT receptors in the brain, but is also expressed on serotonin neurons as an autoreceptor where it plays a critical role in regulating the activity of the entire serotonin system. Over-expression of the 5-HT1A autoreceptor has been implicated in reducing serotonergic neurotransmission, and is associated with major depression and suicide. Extensive characterization of the transcriptional regulation of the 5-HT1A gene (HTR1A) using cell culture systems has revealed a GC-rich "housekeeping" promoter that non-selectively drives its expression; this is flanked by a series of upstream repressor elements for REST, Freud-1/CC2D1A and Freud-2/CC2D1B factors that not only restrict its expression to neurons, but may also regulate the level of expression of 5-HT1A receptors in various subsets of neurons, including serotonergic neurons. A separate set of allele-specific factors, including Deaf1, Hes1 and Hes5 repress at the HTR1A C(-1019)G (rs6295) polymorphism in serotonergic neurons in culture, as well as in vivo. Pet1, an obligatory enhancer for serotonergic differentiation, has been identified as a potent activator of 5-HT1A autoreceptor expression. Taken together, these results highlight an integrated regulation of 5-HT1A autoreceptors that differs in several aspects from regulation of post-synaptic 5-HT1A receptors, and could be selectively targeted to enhance serotonergic neurotransmission.
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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) | 0.001 | 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 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".