DREAM Controls the On/Off Switch of Specific Activity-Dependent Transcription Pathways
Bibliographic record
Abstract
Changes in nuclear Ca(2+) homeostasis activate specific gene expression programs and are central to the acquisition and storage of information in the brain. DREAM (downstream regulatory element antagonist modulator), also known as calsenilin/KChIP-3 (K(+) channel interacting protein 3), is a Ca(2+)-binding protein that binds DNA and represses transcription in a Ca(2+)-dependent manner. To study the function of DREAM in the brain, we used transgenic mice expressing a Ca(2+)-insensitive/CREB-independent dominant active mutant DREAM (daDREAM). Using genome-wide analysis, we show that DREAM regulates the expression of specific activity-dependent transcription factors in the hippocampus, including Npas4, Nr4a1, Mef2c, JunB, and c-Fos. Furthermore, DREAM regulates its own expression, establishing an autoinhibitory feedback loop to terminate activity-dependent transcription. Ablation of DREAM does not modify activity-dependent transcription because of gene compensation by the other KChIP family members. The expression of daDREAM in the forebrain resulted in a complex phenotype characterized by loss of recurrent inhibition and enhanced long-term potentiation (LTP) in the dentate gyrus and impaired learning and memory. Our results indicate that DREAM is a major master switch transcription factor that regulates the on/off status of specific activity-dependent gene expression programs that control synaptic plasticity, learning, and memory.
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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 | 0.001 |
| 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".