Mechanisms of apoptosis induced by purine nucleosides in astrocytes
Bibliographic record
Abstract
Abstract Astrocytes release adenine‐based and guanine‐based purines under physiological and, particularly, pathological conditions. Thus, the aim of this study was to determine if adenosine induced apoptosis in cultured rat astrocytes. Further, if guanosine, which increases the extracellular concentration of adenosine, also induced apoptosis determined using the TUNEL and Annexin V assays. Adenosine induced apoptosis in a concentration‐dependent manner up to 100 μM. Inosine, hypoxanthine, guanine, and guanosine did not. Guanosine or adenosine (100 μM) added to the culture medium was metabolized, with 35% or 15%, respectively, remaining after 2–3 h. Guanosine evoked the extracellular accumulation of adenosine, and particularly of adenine‐based nucleotides. Cotreatment with EHNA and guanosine increased the extracellular accumulation of adenosine and induced apoptosis. Inhibition of the nucleoside transporters using NBTI (100 μM) or propentophylline (100 μM) significantly decreased but did not abolish the apoptosis induced by guanosine + EHNA or adenosine + EHNA, respectively. Apoptosis produced by either guanosine + EHNA or adenosine + EHNA was unaffected by A1 or A2 adenosine receptor antagonists, but was significantly reduced by MRS 1523, a selective A3 adenosine receptor antagonist. Adenosine + EHNA, not guanosine + EHNA, significantly increased the intracellular concentration of S‐adenosyl‐L‐homocysteine (SAH) and greatly reduced the ratio of S‐adenosyl‐L‐methioine to SAH, which is associated with apoptosis. These data demonstrate that adenosine mediates apoptosis of astrocytes both, via activation of A3 adenosine receptors and by modulating SAH hydrolase activity. Guanosine induces apoptosis by accumulating extracellular adenosine, which then acts solely via A3 adenosine receptors. GLIA 38:179–190, 2002. © 2002 Wiley‐Liss, Inc.
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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".