Divergent Roles of IRAK4-Mediated Innate Immune Responses in Two Experimental Models of Severe Malaria
Bibliographic record
Abstract
Severe malaria represents a clinical spectrum of disease. We propose that innate immune inflammatory responses to malaria play key roles in the pathogenesis and clinical outcomes of distinct severe malaria syndromes. To investigate this hypothesis, mice deficient in IRAK4, central to Toll-like receptor (TLR)-mediated signaling, were studied in two experimental models of malaria: Plasmodium berghei (PbA) and Plasmodium chabaudi (PccAS). Irak4(-/-)mice had decreased pro-inflammatory cytokine production during infection in both models. However, animals were relatively protected from PbA-associated symptoms compared with wild-type mice, whereas Irak4(-/-) animals were more susceptible to PccAS-associated disease. These results show that IRAK4-mediated innate immune inflammatory responses play critical roles in divergent clinical outcomes in murine malaria models. As such, integrated approaches, using more than one model, are required to fully understand the parasite/host interactions that characterize severe malaria, and more importantly, to fully assess the effect of adjunctive therapies targeting innate immune responses to malaria.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".