A lactate-dependent shift of glycolysis mediates synaptic and cognitive processes in male mice
Bibliographic record
Abstract
Astrocytes control brain activity via both metabolic processes and gliotransmission, but the physiological links between these functions are scantly known. Here we show that endogenous activation of astrocyte type-1 cannabinoid (CB1) receptors determines a shift of glycolysis towards the lactate-dependent production of d-serine, thereby gating synaptic and cognitive functions in male mice. Mutant mice lacking the CB1 receptor gene in astrocytes (GFAP-CB1-KO) are impaired in novel object recognition (NOR) memory. This phenotype is rescued by the gliotransmitter d-serine, by its precursor l-serine, and also by lactate and 3,5-DHBA, an agonist of the lactate receptor HCAR1. Such lactate-dependent effect is abolished when the astrocyte-specific phosphorylated-pathway (PP), which diverts glycolysis towards l-serine synthesis, is blocked. Consistently, lactate and 3,5-DHBA promoted the co-agonist binding site occupancy of CA1 post-synaptic NMDA receptors in hippocampal slices in a PP-dependent manner. Thus, a tight cross-talk between astrocytic energy metabolism and gliotransmission determines synaptic and cognitive processes. The molecular interplay between metabolic and synaptic functions of astrocytes is underexplored. Here, the authors show that astrocyte cannabinoid type-1 receptors integrate lactate and D-serine signaling to promote NMDA receptor-dependent cognition.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".