A2A adenosine receptor stimulation enhances arginase I expression in macrophages resulting in a phenotypically unique macrophage
Bibliographic record
Abstract
Background. Macrophages traditionally are grouped into two distinct categories, classically (exposed to LPS or Th1 cytokines) or alternatively (exposed to Th2 cytokines) activated macrophages. Adenosine may also modulate macrophage function through G‐protein‐coupled receptors A 1 , A 2A , A 2B , and A 3 . Methods. To understand the effects of adenosine on macrophage function, LPS stimulated macrophages were treated with an agonist for the A 2A receptor (ATL 313). Real time PCR, enzymatic assays, and ELISAs were performed. Results. ATL 313 treatment of LPS stimulated macrophages resulted in a dramatic increase in arginase I expression and enzymatic activity, hallmarks of an alternatively activated macrophage. Expression of other markers of alternatively activated macrophages (Fizz‐1 and YM) were absent in ATL 313 treated cells. In addition, LPS induced expression and activity of iNOS in macrophages were not affected by ATL 313. Conclusion. We propose stimulation of the A 2A receptor increases arginase activity, thus altering arginine metabolism resulting in increased production of polyamines and proline. This stimulation results in a unique macrophage phenotype that may promote cellular proliferation and wound healing and inhibit T lymphocyte responses. Supported by NIH AI070491.
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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".