Activation of Mast Cells Promote Plasmodium berghei ANKA Infection in Murine Model
Bibliographic record
Abstract
Malaria, a mosquito-borne infectious disease, is a severe health problem worldwide. As reported, some anti-malarial drugs with anti-parasitic properties also block mast cells (MCs) activities. It is hypothesized that MCs activity may be correlated with the pathogenesis of malaria. Thus, the role of MCs on malarial pathogenesis and the involved physiological action and pathways need to be further investigated. This study aimed to investigate the effect of MCs activation on malaria disease severity using KunMing mice with Plasmodium berghei ANKA (PbANKA) infection treated with MCs degranulator (compound 48/80, C48/80) or MCs stabilizer (disodium cromoglycate, DSCG). PbANKA infection caused a dramatic increase in MCs density and level of MCs degranulation in cervical lymph node (CLN) and skin. Compared with infected control, C48/80 treatment had shortened survival time, increased parasitemia, exacerbated liver inflammation and CLN hyperplasia, accompanied with increase in vascular leakage and leukocyte number. The infected mice with C48/80 treatment also elevated the release of CCL2, CXCL1, and MMP-9 from MCs in CLN and skin, and TNF-α, IFN-γ, CCR2 and CXCR2 mRNA expression in CLN and liver. In contrast, the infected mice treated with DSCG showed longer survival time, lower parasitemia, improved liver inflammation and CLN hyperplasia, followed by a decline of vascular leakage and leukocyte number. Decreased MCs-derived CCL2, CXCL1, and MMP-9 from CLN and skin, mRNA expression in CLN and liver (TNF-α, IFN-γ, CCR2 and CXCR2) were also observed in infected mice with DSCG treatment. Our data indicated that MCs activation may facilitate the pathogenesis of PbANKA infection.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".