A1 Adenosine Receptor Upregulation and Activation Attenuates Neuroinflammation and Demyelination in a Model of Multiple Sclerosis
Why this work is in the frame
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Bibliographic record
Abstract
The neuromodulator adenosine regulates immune activation and neuronal survival through specific G-protein-coupled receptors expressed on macrophages and neurons, including the A1 adenosine receptor (A1AR). Here we show that A1AR null (A1AR-/-) mice developed a severe progressive-relapsing form of experimental allergic encephalomyelitis (EAE) compared with their wild-type (A1AR+/+) littermates. Worsened demyelination, axonal injury, and enhanced activation of microglia/macrophages were observed in A1AR-/- animals. In addition, spinal cords from A1AR-/- mice demonstrated increased proinflammatory gene expression during EAE, whereas anti-inflammatory genes were suppressed compared with A1AR+/+ animals. Macrophages from A1AR-/- animals exhibited increased expression of the proinflammatory genes, interleukin-1beta, and matrix metalloproteinase-12 on immune activation when matched with A1AR+/+ control cells. A1AR-/- macrophage-derived soluble factors caused significant oligodendrocyte cytotoxicity compared with wild-type controls. The A1AR was downregulated in microglia in A1AR+/+ mice during EAE accompanied by neuroinflammation, which recapitulated findings in multiple sclerosis (MS) patients. Caffeine treatment augmented A1AR expression on microglia, with ensuing reduction of EAE severity, which was further enhanced by concomitant treatment with the A1AR agonist, adenosine amine congener. Thus, modulation of neuroinflammation by the A1AR represents a novel mechanism that provides new therapeutic opportunities for MS and other demyelinating diseases.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.003 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it