Freud-2/CC2D1B mediates dual repression of the serotonin-1A receptor gene
Bibliographic record
Abstract
The serotonin-1A (5-HT1A) receptor functions as a pre-synaptic autoreceptor in serotonin neurons that regulates their activity, and is also widely expressed on non-serotonergic neurons as a post-synaptic heteroreceptor to mediate serotonin action. The 5-HT1A receptor gene is strongly repressed by a dual repressor element (DRE), which is recognized by two proteins: Freud-1/CC2D1A and another unknown protein. Here we identify mouse Freud-2/CC2D1B as the second repressor of the 5-HT1A-DRE. Freud-2 shares 50% amino acid identity with Freud-1, and contains conserved structural domains. Mouse Freud-2 bound specifically to the rat 5-HT1A-DRE adjacent to, and partially overlapping, the Freud-1 binding site. By supershift assay using nuclear extracts from L6 myoblasts, Freud-2-DRE complexes were distinguished from Freud-1-DRE complexes. Freud-2 mRNA and protein were detected throughout mouse brain and peripheral tissues. Freud-2 repressed 5-HT1A promoter-reporter constructs in a DRE-dependent manner in non-neuronal (L6) or 5-HT1A-expressing neuronal (NG108-15, RN46A) cell models. In NG108-15 cells, knockdown of Freud-2 using a specific short-interfering RNA reduced endogenous Freud-2 protein levels and decreased Freud-2 bound to the 5-HT1A-DRE as detected by chromatin immunoprecipitation assay, but increased 5-HT1A promoter activity and 5-HT1A protein levels. Taken together, these data show that Freud-2 is the second component that, with Freud-1, mediates dual repression of the 5-HT1A receptor gene at the DRE.
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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) | 0.001 | 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 | 0.001 |
| 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".