A role for neuronal cAMP responsive-element binding (CREB)-1 in brain responses to calorie restriction
Bibliographic record
Abstract
Calorie restriction delays brain senescence and prevents neurodegeneration, but critical regulators of these beneficial responses other than the NAD(+)-dependent histone deacetylase Sirtuin-1 (Sirt-1) are unknown. We report that effects of calorie restriction on neuronal plasticity, memory and social behavior are abolished in mice lacking cAMP responsive-element binding (CREB)-1 in the forebrain. Moreover, CREB deficiency drastically reduces the expression of Sirt-1 and the induction of genes relevant to neuronal metabolism and survival in the cortex and hippocampus of dietary-restricted animals. Biochemical studies reveal a complex interplay between CREB and Sirt-1: CREB directly regulates the transcription of the sirtuin in neuronal cells by binding to Sirt-1 chromatin; Sirt-1, in turn, is recruited by CREB to DNA and promotes CREB-dependent expression of target gene peroxisome proliferator-activated receptor-γ coactivator-1α and neuronal NO Synthase. Accordingly, expression of these CREB targets is markedly reduced in the brain of Sirt KO mice that are, like CREB-deficient mice, poorly responsive to calorie restriction. Thus, the above circuitry, modulated by nutrient availability, links energy metabolism with neurotrophin signaling, participates in brain adaptation to nutrient restriction, and is potentially relevant to accelerated brain aging by overnutrition and diabetes.
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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 | 0.001 |
| 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".