Role of Host Protein Tyrosine Phosphatase SHP-1 in<i>Leishmania donovani</i>-Induced Inhibition of Nitric Oxide Production
Bibliographic record
Abstract
In order to survive within the macrophages of its host organism, the protozoan parasite Leishmania inhibits a number of critical, gamma interferon (IFN-gamma)-inducible, macrophage functions, including the generation of nitric oxide. We have previously shown that the protein tyrosine phosphatase SHP-1 (Src-homology 2 domain containing phosphatase-1) is activated during Leishmania infection and plays an important role in both the survival of Leishmania within cultured macrophages and disease progression in vivo by inhibiting nitric oxide production. Here we use a SHP-1-/- macrophage cell line derived from motheaten mice to address the mechanisms by which SHP-1 prevents IFN-gamma-dependent nitric oxide production during Leishmania donovani infection. We show that Leishmania inhibits nitric oxide production in response to IFN-gamma poorly in SHP-1-deficient macrophages. This correlates with the inability of Leishmania to alter JAK2 and mitogen-activated protein kinase extracellular signal-regulated kinase 1 and 2 (ERK1/2) phosphorylation and to prevent nuclear translocation of transcription factors NF-kappaB and AP-1, although the latter two to a lesser extent. Surprisingly, Leishmania inactivated the transcription factor STAT1 to a similar extent in SHP-1-deficient and wild-type macrophages, so STAT1 is not necessary for nitric oxide production by infected macrophages. Overall, this study demonstrates that induction of SHP-1 by Leishmania is vital for inhibition of nitric oxide generation and that this inhibition occurs through the inactivation of JAK2 and ERK1/2, and transcription factors NF-kappaB and AP-1.
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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".