Differential Roles of CD36, ICAM‐1, and P‐selectin in <i>Plasmodium falciparum</i> Cytoadherence In Vivo
Bibliographic record
Abstract
Cytoadherence of Plasmodium falciparum-infected red blood cells (IRBCs) on human microvascular endothelium is mediated by synergistic adhesive interactions with different adhesion molecules in vitro. Here, the authors used a unique human/severe combined immunodeficient (SCID) mouse chimeric model to directly visualize IRBC-endothelial interactions in an intact human microvasculature in vivo. Stimulation of human skin grafts with 100 ng TNF-alpha for 4 h led to a dramatic reduction in the distance rolled by IRBCs before arrest, so that the majority of IRBCs adhered directly to the endothelium with a 1.8-fold increase in the number of adherent cells. The decrease in rolling distance and increase in adhesion could be reversed by anti-ICAM-1. More importantly, the effect of TNF-alpha could be seen only in the presence of CD36. A further increase in adhesion by 4.9-fold was observed after 24 h of TNF-alpha stimulation. The increase could be reversed by anti-ICAM-1, but not anti-VCAM-1. In histamine-stimulated grafts, the rolling flux fraction and adhesion increased by 2.8- and 1.6-fold, respectively. The increases were attributable to P-selectin as an inhibitory anti-P-selectin antibody abrogated both the increased rolling flux fraction and firm adhesion. These findings indicate that in addition to CD36, ICAM-1, and P-selectin are major contributors to the dynamic process of IRBC adhesion by different mechanisms in vivo.
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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".