CD47-SIRPα Interactions Regulate Macrophage Uptake of Plasmodium falciparum-Infected Erythrocytes and Clearance of Malaria <i>In Vivo</i>
Bibliographic record
Abstract
CD47 engagement by the macrophage signal regulatory protein alpha (SIRPα) inhibits phagocytic activity and protects red blood cells (RBCs) from erythrophagocytosis. The role of CD47-SIRPα in the innate immune response to Plasmodium falciparum infection is unknown. We hypothesized that disruption of SIRPα signaling may enhance macrophage uptake of malaria parasite-infected RBCs. To test this hypothesis, we examined in vivo clearance in CD47-deficient mice infected with Plasmodium berghei ANKA and in vitro phagocytosis of P. falciparum-infected RBCs by macrophages from SHP-1-deficient (Shp-1(-/-)) mice and NOD.NOR-Idd13.Prkdc(scid) (NS-Idd13) mice, as well as human macrophages, following disruption of CD47-SIRPα interactions with anti-SIRPα antibodies or recombinant SIRPα-Fc fusion protein. Compared to their wild-type counterparts, Cd47(-/-) mice displayed significantly lower parasitemia, decreased endothelial activation, and enhanced survival. Using macrophages from SHP-1-deficient mice or from NS-Idd13 mice, which express a SIRPα variant that does not bind human CD47, we showed that altered SIRPα signaling resulted in enhanced phagocytosis of P. falciparum-infected RBCs. Moreover, disrupting CD47-SIRPα engagement using anti-SIRPα antibodies or SIRPα-Fc fusion protein also increased phagocytosis of P. falciparum-infected RBCs. These results indicate an important role for CD47-SIRPα interactions in innate control of malaria and suggest novel targets for intervention.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".