Role of SLC11A1 (formerly NRAMP1) in regulation of signal transduction induced by Toll-like receptor 7 ligands
Bibliographic record
Abstract
Modulation of immune responses using Toll-like receptor (TLR) ligands is fast becoming one of the main new approaches for the treatment of infectious and allergic diseases. Characterizing the role of genetic factors in modulating responses to these ligands will be crucial in determining the efficacy of a particular treatment. Our previous findings have shown that treatment of Mycobacterium bovis BCG infection with a synthetic TLR7 ligand resulted in a reduction of the splenic bacterial load only in mice carrying a wild-type allele of Nramp1. To understand further how natural resistance-associated macrophage protein 1 (NRAMP1) modulates responses to TLR7 ligands, we have analysed various important TLR7 signal transduction events in macrophage cell lines derived from B10.ANramp1r and B10.ANramp1-/- mice. The Nramp1 genotype did not affect TLR7 receptor expression, ligand uptake or intracellular processing. Following TLR7 ligand stimulation, p38 mitogen-activated protein kinase (MAPK) activation was significantly reduced in B10A.Nramp1-/- macrophages compared with B10A.Nramp1r cells. Interestingly, levels of protein kinase C zeta (PKCzeta) activation were also found to be lower in B10A.Nramp1-/- macrophages and inhibition of this kinase in B10A.Nramp1r cells led to a reduction in cytokine production. Taken together, the data demonstrate a role for NRAMP1 in modulating p38 MAPK and PKCzeta activity, which leads to reduced cytokine induction by TLR7 ligands.
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How this classification was reachedexpand
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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 teacher head, 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".