Glutamate Transporter Coupling to Na,K-ATPase
Bibliographic record
Abstract
Deactivation of glutamatergic signaling in the brain is mediated by glutamate uptake into glia and neurons by glutamate transporters. Glutamate transporters are sodium-dependent proteins that putatively rely indirectly on Na,K-ATPases to generate ion gradients that drive transmitter uptake. Based on anatomical colocalization, mutual sodium dependency, and the inhibitory effects of the Na,K-ATPase inhibitor ouabain on glutamate transporter activity, we postulated that glutamate transporters are directly coupled to Na,K-ATPase and that Na,K-ATPase is an essential modulator of glutamate uptake. Na,K-ATPase was purified from rat cerebellum by tandem anion exchange and ouabain affinity chromatography, and the cohort of associated proteins was characterized by mass spectrometry. The alpha1-alpha 3 subunits of Na,K-ATPase were detected, as were the glutamate transporters GLAST and GLT-1, demonstrating that glutamate transporters copurify with Na,K-ATPases. The link between glutamate transporters and Na,K-ATPase was further established by coimmunoprecipitation and colocalization. Analysis of the regulation of glutamate transporter and Na,K-ATPase activities was assessed using [(3)H]D-aspartate, [(3)H]L-glutamate, and rubidium-86 uptake into synaptosomes and cultured astrocytes. In synaptosomes, ouabain produced a dose-dependent inhibition of glutamate transporter and Na,K-ATPase activities, whereas in astrocytes, ouabain showed a bimodal effect whereby glutamate transporter activity was stimulated at 1 microm ouabain and inhibited at higher concentrations. The effects of protein kinase inhibitors on [(3)H]D-aspartate uptake indicated the selective involvement of Src kinases, which are probably a component of the Na,K-ATPase/glutamate transporter complex. These findings demonstrate that glutamate transporters and Na,K-ATPases are part of the same macromolecular complexes and operate as a functional unit to regulate glutamatergic neurotransmission.
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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 | 0.001 | 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".