Regulator of Calcineurin 1 Modulates Expression of Innate Anxiety and Anxiogenic Responses to Selective Serotonin Reuptake Inhibitor Treatment
Bibliographic record
Abstract
Regulator of calcineurin 1 (RCAN1) controls the activity of calcium/calmodulin-dependent phosphatase calcineurin (CaN), which has been implicated in human anxiety disorders. Previously, we reported that RCAN1 functioned as an inhibitor of CaN activity in the brain. However, we now find enhanced phosphorylation of a CaN substrate, cAMP response element-binding protein (CREB), in the brains of Rcan1 knock-out (KO) mice. Consistent with enhanced CREB activation, we also observe enhanced expression of a CREB transcriptional target, brain-derived neurotrophic factor (BDNF) in Rcan1 KO mice. We also discovered that RCAN1 deletion or blockade of RCAN1-CaN interaction reduced CaN and protein phosphatase-1 localization to nuclear-enriched protein fractions and promoted CREB activation. Because of the potential links between CREB, BDNF, and anxiety, we examined the role of RCAN1 in the expression of innate anxiety. Rcan1 KO mice displayed reduced anxiety in several tests of unconditioned anxiety. Acute pharmacological inhibition of CaN rescued these deficits while transgenic overexpression of human RCAN1 increased anxiety. Finally, we found that Rcan1 KO mice lacked the early anxiogenic response to the selective serotonin reuptake inhibitor (SSRI) fluoxetine and had improved latency for its therapeutic anxiolytic effects. Together, our study suggests that RCAN1 plays an important role in the expression of anxiety-related and SSRI-related behaviors through CaN-dependent signaling pathways. These results identify RCAN1 as a mediator of innate emotional states and possible therapeutic target for anxiety.
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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 | 0.001 |
| 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 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".