Diminished adenosine A1 receptor expression on macrophages in brain and blood of patients with multiple sclerosis
Bibliographic record
Abstract
The nucleoside adenosine has been shown to control the production of proinflammatory molecules through its actions on cell surface purine receptors. Previously, we have reported that the adenosine A1 receptor (A1AR) regulates tumor necrosis factor-alpha (TNF-alpha) and interleukin-6 (IL-6) expression and exhibits diminished function in patients with multiple sclerosis (MS; Mayne et al., Ann Neurol 1999;45:633-639). In the present study, A1AR expression in both brain and peripheral blood mononuclear cells (PBMC) from MS and control groups was characterized by fluorescence-activated cell sorting (FACS), reverse transcriptase-polymerase chain reaction (RT-PCR), and immunohistochemical analyses. FACS analyses of PBMC revealed that A1AR expression was chiefly detectable on CD14-positive cells and was reduced by 53.1% (p < 0.01) in MS patients compared to controls. A1AR mRNA levels were reduced by 43.1% (p < 0.001) in the brains of MS patients compared to patients with other neurological diseases and controls. A1AR protein expression in brain was detected primarily in CD45-positive glial cells and was markedly diminished in MS patients. The analysis of A1AR transcripts in the brain revealed that the A1AR-beta transcript was diminished (49.2%) in MS patients compared to controls (p < 0.002). These results indicate that the A1AR, expressed principally on cells of monocyte/macrophage lineage in both brain and blood, is selectively diminished in MS patients. Reduction of the A1AR-beta transcript in MS patients suggests that dysregulated splicing may influence A1AR protein levels, potentially leading to increased macrophage activation and central nervous system inflammation.
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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 | 0.001 | 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".