RNA interference reveals a role for TLR2 and TLR3 in the recognition of <i>Leishmania donovani</i> promastigotes by interferon–γ‐primed macrophages
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
Leishmania donovani promastigotes evade the induction of a proinflammatory response during their invasion of naive macrophages. However, their entry into IFN-gamma-primed macrophages is accompanied by the secretion of nitric oxide (NO) and proinflammatory cytokines. In the present study, we addressed the hypothesis that priming with IFN-gamma induces the expression of a receptor that enables mouse macrophages to recognize L. donovani promastigotes. We observed that in IFN-gamma-primed macrophages, L. donovani promastigotes stimulated Interleukin-1 receptor-associated kinase-1 (IRAK-1) activity. We next showed that Toll-like receptor (TLR)3 is barely detectable in naive macrophages but is expressed in IFN-gamma-treated macrophages. Silencing of TLR3, TLR2, IRAK-1 and myeloid differentiation factor 88 (MyD88) expression by RNA interference revealed that both TLR are involved in the secretion of NO and TNF-alpha induced by L. donovani promastigotes. Using L. donovani mutants, we showed that TLR2-mediated responses are dependent on Galbeta1,4Manalpha-PO(4)-containing phosphoglycans, whereas TLR3-mediated responses are independent of these glycoconjugates. Furthermore, our data indicate a participation of TLR2 and TLR3 in the phagocytosis of L. donovani promastigotes and a role for TLR3 in the leishmanicidal activity of the IFN-gamma-primed macrophages. Collectively, our data are consistent with a model where recognition of L. donovani promastigotes depends on the macrophage activation status and requires the expression of TLR3.
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 | 0.002 | 0.001 |
| 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 it