Purinergic P2X<sub>7</sub> receptor function in lung alveolar macrophages: Pharmacologic characterization and bidirectional regulation by Th1 and Th2 cytokines
Bibliographic record
Abstract
Abstract Purinergic P2X7 receptors have been shown in the lung, but little is known concerning P2X7 function in pulmonary macrophages. In this study we characterized P2X7‐dependent responses to extracellular ATP in resident and activated alveolar macrophages (AM) obtained by bronchoalveolar lavage of rats. Incubation of AM with high concentrations of ATP (5mM) or 3′‐O‐(4‐benzoyl)benzoyl‐ATP (BzATP) (0.5mM), a P2X7 agonist, induced: 1) rapid pore formation, 2) apoptosis, and 3) enhanced release of IL‐1α, IL‐1β, and IL‐6, but not TNF‐α following priming with lipopolysaccharide (LPS). Furthermore, higher expression of P2X7 receptor in AM was associated with increased formation of Type 2 multinucleated giant cells (Type 2 MGC) in response to GMCSF. Immunopharmacological analysis also showed that P2X7‐dependent pore formation in AM was significantly increased by LPS (1 µg/ml) and the T helper 1 (Th1) cytokines, interferon‐γ (100U/ml), and, to a lesser extent, TNF‐α (>20 ng/ml). In contrast, the T helper 2 (Th2) cytokines IL‐4 (1pg/ml) as well as IL‐10 (1ng/ml) significantly inhibited these P2X7 receptor functions. Transforming growth factor‐β (TGF‐β), a known deactivator of macrophages, had no significant effect. Our results demonstrate that AM exhibit all the characteristics of a functional P2X7 receptor which upon appropriate stimulation activates the proinflammatory IL‐1→IL‐6 cytokine cascade and the formation of MGC, a hallmark of granulomatous reactions. Moreover, Th1 and Th2 cytokines reciprocally regulate P2X7 function, suggesting a role for P2X7 in pulmonary diseases associated with chronic inflammatory responses. Drug Dev. Res. 59:118–127, 2003. © 2003 Wiley‐Liss, Inc.
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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".