Malarial Hemozoin Activates the NLRP3 Inflammasome through Lyn and Syk Kinases
Bibliographic record
Abstract
The intraerythrocytic parasite Plasmodium -- the causative agent of malaria -- produces an inorganic crystal called hemozoin (Hz) during the heme detoxification process, which is released into the circulation during erythrocyte lysis. Hz is rapidly ingested by phagocytes and induces the production of several pro-inflammatory mediators such as interleukin-1beta (IL-1beta). However, the mechanism regulating Hz recognition and IL-1beta maturation has not been identified. Here, we show that Hz induces IL-1beta production. Using knockout mice, we showed that Hz-induced IL-1beta and inflammation are dependent on NOD-like receptor containing pyrin domain 3 (NLRP3), ASC and caspase-1, but not NLRC4 (NLR containing CARD domain). Furthermore, the absence of NLRP3 or IL-1beta augmented survival to malaria caused by P. chabaudi adami DS. Although much has been discovered regarding the NLRP3 inflammasome induction, the mechanism whereby this intracellular multimolecular complex is activated remains unclear. We further demonstrate, using pharmacological and genetic intervention, that the tyrosine kinases Syk and Lyn play a critical role in activation of this inflammasome. These findings not only identify one way by which the immune system is alerted to malarial infection but also are one of the first to suggest a role for tyrosine kinase signaling pathways in regulation of the NLRP3 inflammasome.
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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".