Lipoxin A <sub>4</sub> and aspirin-triggered 15-epi-lipoxin A <sub>4</sub> inhibit peroxynitrite formation, NF-κB and AP-1 activation, and IL-8 gene expression in human leukocytes
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Lipoxin A(4) (LXA(4)) and aspirin-triggered 15-epi-LXA(4) (ATL) are emerging as endogenous braking signals for neutrophil-mediated tissue injury. Recent studies indicate that peroxynitrite (ONOO(-)) may function as an intracellular signal for the production of IL-8, a potent proinflammatory cytokine in human leukocytes. In this study, we evaluated the impact of the metabolically stable analogues of LXA(4)/ATL on lipopolysaccharide (LPS)-induced ONOO(-) formation and ONOO(-)-mediated IL-8 gene expression in human leukocytes. At nanomolar concentrations, LXA(4) analogues markedly reduced LPS-stimulated superoxide formation, evoked increases in intracellular diamino-fluorescein fluorescence (an indicator of NO formation), and consequently reduced ONOO(-) formation in isolated neutrophils, as well as in neutrophils, monocytes, and lymphocytes, in whole blood. LXA(4)/ATL analogues attenuated nuclear accumulation of activator protein-1 and nuclear factor-kappaB in both polymorphonuclear and mononuclear leukocytes and inhibited IL-8 mRNA expression and IL-8 release by 50-65% in response to LPS. The LXA(4) inhibitory responses were concentration dependent and were not shared by 15-deoxy-LXA(4). None of the LXA(4) analogues studied affected neutrophil survival, nor reversed the apoptosis delaying action of LPS in neutrophils. In addition, LXA(4) analogues had no significant effect on exogenous ONOO(-)-induced IL-8 gene and protein expression. These findings suggest that by attenuating ONOO(-) formation, LXA(4) and ATL can oppose ONOO(-) signaling in leukocytes and provide a rationale for using stable synthetic analogues as antiinflammatory compounds in vivo.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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