Astrocytes and neurons: different roles in regulating adenosine levels
Bibliographic record
Abstract
OBJECTIVES: Adenosine is an endogenous nucleoside that signals through G-protein coupled receptors. Extracellular adenosine is required for receptor activation and two pathways have been identified for formation and cellular release of adenosine. The CLASSICAL pathway relies on intracellular formation of adenosine from adenine nucleotides and cellular efflux of adenosine via equilibrative nucleoside transporters (ENTs). The ALTERNATE pathway involves cellular release of adenine nucleotides, hydrolysis via ecto-5'-nucleotidases and extracellular formation of adenosine. METHODS: A rat model of cerebral ischemia and primary cultures of rat forebrain astrocytes and neurons were used. RESULTS: Using a rat model of cerebral ischemia, the ENT1 inhibitor nitrobenzylmercaptopurine ribonucleoside (NBMPR) significantly increased post-ischemic forebrain adenosine levels and significantly decreased hippocampal neuron injury relative to saline-treatment. NBMPR-induced increases in adenosine receptor activation were not detected, suggesting that altering the intracellular:extracellular distribution of adenosine can affect ischemic outcome. Using primary cultures of rat forebrain astrocytes and neurons, adenosine release was evoked by ischemic-like conditions. Dipyridamole, an inhibitor of ENTs, was more effective at inhibiting adenosine release from neurons than from astrocytes. In contrast, alpha , beta-methylene ADP, an inhibitor of ecto-5'-nucleotidase, was effective at inhibiting adenosine release from astrocytes, but not from neurons. Thus, during ischemic-like conditions, neurons released adenosine via the CLASSICAL pathway, while astrocytes released adenosine via the ALTERNATE pathway. DISCUSSION: These cell type differences in pathways for adenosine formation during ischemia may allow transport inhibitors to block simultaneously adenosine release from neurons and adenosine uptake into astrocytes. In principle, this could improve neuronal ATP levels without decreasing adenosine receptor activation.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".