Regulation of macrophage nitric oxide production by the protein tyrosine phosphatase Src homology 2 domain phosphotyrosine phosphatase 1 (SHP‐1)
Bibliographic record
Abstract
Nitric oxide (NO) is a potent molecule involved in the cytotoxic effects mediated by macrophages (MØ) against microorganisms. We previously reported that Src homology 2 domain phosphotyrosine phosphatase 1 (SHP-1)-deficient cells generate a greater amount of NO than wild-type cells in response to interferon-gamma (IFN-gamma). We also reported that the Leishmania-induced MØ SHP-1 activity is needed for the survival of the parasite within phagocytes through the attenuation of NO-dependent and NO-independent mechanisms. In the present study, we investigated the role of SHP-1 in regulating key signalling molecules important in MØ NO generation. Janus tyrosine kinase 2 (JAK2), mitogen-activated extracellular signal-regulated protein kinase kinase (MEK), extracellular signal-regulated kinases 1 and 2 (Erk1/Erk2) mitogen-activated protein kinases, p38 and stress-activated mitogen-activated protein kinases/c-Jun NH(2)-terminal kinase (SAPK/JNK) were examined in immortalized bone marrow-derived MØ (BMDM) from both SHP-1-deficient motheaten mice (me-3) and their respective littermates (LM-1). The results indicated that Erk1/Erk2 and SAPK/JNK are the main kinases regulated by SHP-1 because the absence of SHP-1 caused an increase in their phosphorylation. Moreover, only Apigenin, the specific inhibitor of Erk1/Erk2, was able to block IFN-gamma-induced inducible nitric oxide synthase (iNOS) transcription and translation in me-3 cells. Transcription factor analyses revealed that in the absence of SHP-1, activator protein-1 (AP-1) was activated. The activation of AP-1, and not nuclear factor-kappaB (NF-kappaB) or signal transducer and activator of transcription-1 alpha (STAT-1 alpha), may explain the enhanced NO generation in SHP-1-deficient cells. These observations emphasize the involvement of the MAPKs Erk1/Erk2 and SAPK/JNK in NO generation via AP-1 activation. Collectively, our findings suggest that SHP-1 plays a pivotal role in the negative regulation of signalling events leading to iNOS expression and NO generation. Furthermore, our observations underline the importance of SHP-1-mediated negative regulation in maintaining NO homeostasis and thus preventing the abnormal generation of NO that can be detrimental to the host.
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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) | 0.000 | 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 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".