Signalling events involved in interferon‐γ‐inducible macrophage nitric oxide generation
Why this work is in the frame
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Bibliographic record
Abstract
Nitric oxide (NO) produced by macrophages (Mphi) in response to interferon-gamma (IFN-gamma) plays a pivotal role in the control of intracellular pathogens. Current knowledge of the specific biochemical cascades involved in this IFN-gamma-inducible Mphi function is still limited. In the present study, we evaluated the participation of various second messengers--Janus kinase 2 (JAK2), signal transducer and activator of transcription (STAT) 1alpha, MAP kinase kinase (MEK1/2), extracellular signal-regulated kinases 1 and 2 (Erk1/Erk2) and nuclear factor kappa B (NF-kappaB)--in the regulation of NO production by IFN-gamma-stimulated J774 murine Mphi. The use of specific signalling inhibitors permitted us to establish that JAK2/STAT1alpha- and Erk1/Erk2-dependent pathways are the main players in IFN-gamma-inducible Mphi NO generation. To determine whether the inhibitory effect was taking place at the pre- and/or post-transcriptional level, we evaluated the effect of each antagonist on inducible nitric oxide synthase (iNOS) gene and protein expression, and on the capacity of IFN-gamma to induce JAK2, Erk1/Erk2 and STAT1alpha phosphorylation. All downregulatory effects occurred at the pretranscriptional level, except for NF-kappaB, which seems to exert its role in NO production through an iNOS-independent event. In addition, electrophoretic mobility shift assay (EMSA) analysis revealed that STAT1alpha is essential for IFN-gamma-inducible iNOS expression and NO production, whereas the contribution of NF-kappaB to this cellular regulation seems to be minimal. Moreover, our data suggest that Erk1/Erk2 are responsible for STAT1alpha Ser727 residue phosphorylation in IFN-gamma-stimulated Mphi, thus contributing to the full activation of STAT1alpha. Taken together, our results indicate that JAK2, MEK1/2, Erk1/Erk2 and STAT1alpha are key players in the IFN-gamma-inducible generation of NO by Mphi.
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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 | 0.000 |
| 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 it