Blockade of A<sub>2A</sub> adenosine receptors prevents basic fibroblast growth factor‐induced reactive astrogliosis in rat striatal primary astrocytes
Bibliographic record
Abstract
Previous literature data show that blockade of A(2A) adenosine receptors via selective antagonists induces protection in various models of neurodegenerative diseases. The mechanisms underlying this effect are still largely unknown. Since it is known that excessive reactive astrogliosis is a factor contributing to cell death in diseases characterized by neurodegenerative events, the present study has been aimed at determining whether selective A(2A) receptor antagonists can counteract the formation of reactive astrocytes induced in vitro by basic fibroblast growth factor (bFGF), a typical trigger of this reaction. Exposure of primary rat striatal astrocytes to the selective A(2A) antagonist SCH58261 resulted in concentration-dependent abolition of bFGF induction of astrogliosis in vitro. This effect could also be reproduced with the chemically unrelated A(2A) antagonist KW-6002. The direct activation of A(2A) adenosine receptors by selective receptor agonists was not sufficient per se to induce astrogliosis, suggesting that the A(2A) receptor needs to act in concert with other bFGF-induced genes to trigger the formation of reactive astrocytes. These results provide a mechanism at the basis of the neuroprotection induced by A(2A) receptor antagonists in models of brain damage and highlight this adenosine receptor subtype as a novel target for the pharmacological modulation of the gliotic reaction.
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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 | 0.000 |
| 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 | 0.001 |
| 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".