Ethanol Tolerance Affects Endogenous Adenosine Signaling in Mouse Hippocampus
Bibliographic record
Abstract
Ethanol has many pharmacological effects, including increases in endogenous adenosine levels and adenosine receptor activity in brain. Ethanol consumption is associated with both positive and negative health outcomes, but tolerance to the behavioral effects of ethanol can lead to increased consumption, which increases the risk of negative health outcomes. The present study was performed to test whether a 7-day treatment with ethanol is linked to reduced adenosine signaling and whether this is a consequence of reduced ecto-5'-nucleotidase activity. Wild-type (CD73(+/+)) and ecto-5'-nucleotidase-deficient (CD73(-/-)) mice were treated with ethanol (2 g/kg) or saline for 7 days. In CD73(+/+) mice, repeated ethanol treatment reduced the hypothermic and ataxic effects of acute ethanol, indicating the development of tolerance to the acute effects of ethanol. In CD73(+/+) mice, this 7-day ethanol treatment led to increased hippocampal synaptic activity and reduced adenosine A1 receptor activity under both basal and low Mg(2+) conditions. These effects of ethanol tolerance were associated with an 18% decrease in activity of ecto-5'-nucleotidase activity in hippocampal cell membranes. In contrast, ethanol treatment was not associated with changes in synaptic activity or adenosine signaling in hippocampus from CD73(-/-) mice. These data indicate that ethanol treatment is associated with a reduction in adenosine signaling through adenosine A1 receptors in hippocampus, mediated, at least in part, via reduced ecto-5'-nucleotidase activity.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".