Calcium-independent lipid release from astrocytes modulates neuronal excitability
Bibliographic record
Abstract
ABSTRACT An accumulating amount of data suggests that Ca 2+ -dependent gliotransmitter release plays a key role in the modulation of neuronal networks. Here, we tested the hypothesis that in response to agonist exposure, astrocytes release lipid modulators through activation of Ca 2+ -independent phospholipase A 2 (iPLA 2 ) activity. We found that cultured rat astrocytes treated with selective ATP and glutamatergic agonists released arachidonic acid (AA) and/or its derivatives, including the endogenous cannabinoid 2-arachidonoyl-sn-glycerol (2AG) and prostaglandin E2 (PGE 2 ). Surprisingly, the buffering of cytosolic Ca 2+ resulted in a sharp increase in agonist-induced lipid release by astrocytes. In addition, the astrocytic release of PGE 2 increased miniature excitatory postsynaptic potentials (mEPSPs) by inhibiting the opening of neuronal Kv channels in brain slices. This study provides the first evidence showing that a Ca 2+ -independent pathway regulates the release of PGE 2 from astrocytes and further demonstrates the functional role of astrocytic lipid release in the modulation of synaptic activity. SIGNIFICANCE Until now, most studies that implicate astrocytes in the modulation of synaptic activity have focused on Ca 2+ -dependent release of traditional gliotransmitters such as D-serine, ATP, and glutamate. Mobilization of intracellular stores of Ca 2+ occurs within a matter of seconds, but this novel Ca 2+ -independent lipid pathway in astrocytes could occur on a faster time scale and thus play a role in the rapid signaling processes involved in synaptic potentiation, attention, and neurovascular coupling.
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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 | 0.000 |
| 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".