Recruited monocytes modulate malaria-induced lung injury through CD36-mediated clearance of sequestered infected erythrocytes
Bibliographic record
Abstract
Pulmonary complications occur in a significant percentage of adults and children during the course of severe malaria. The cellular and molecular innate immune mechanisms that limit the extent of pulmonary inflammation and preserve lung function during severe Plasmodium infections remain unclear. In particular, the contributions to pulmonary complications by parasitized erythrocyte sequestration and subsequent clearance from the lung microvasculature by immune cells have not been clearly defined. We used the Plasmodium berghei ANKA-C57BL/6 mouse model of severe malaria to investigate the mechanisms governing the nature and extent of malaria-associated lung injury. We have demonstrated that sequestration of infected erythrocytes on postcapillary endothelial surfaces results in acute lung injury and the rapid recruitment of CCR2(+)CD11b(+)Ly6C(hi) monocytes from the circulation. These recruited cells remain in the lungs as monocyte-derived macrophages and are instrumental in the phagocytic clearance of adherent Plasmodium berghei-infected erythrocytes. In contrast, alveolar macrophages do not play a significant role in the clearance of malaria-infected cells. Furthermore, the results obtained from Ccr2(-/-), Cd36(-/-), and CD36 bone marrow chimeric mice showed that sequestration in the absence of CD36-mediated phagocytic clearance by monocytes leads to exaggerated lung pathologic features. In summary, our data indicate that the intensity of malaria-induced lung pathologic features is proportional to the steady-state levels of Plasmodium-infected erythrocytes adhering to the pulmonary vasculature. Moreover, the present work has defined a major role of recruited monocytes in clearing infected erythrocytes from the pulmonary interstitium, thus minimizing lung damage.
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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".