Intravital Observation of Plasmodium berghei Sporozoite Infection of the Liver
Bibliographic record
Abstract
Plasmodium sporozoite invasion of liver cells has been an extremely elusive event to study. In the prevailing model, sporozoites enter the liver by passing through Kupffer cells, but this model was based solely on incidental observations in fixed specimens and on biochemical and physiological data. To obtain direct information on the dynamics of sporozoite infection of the liver, we infected live mice with red or green fluorescent Plasmodium berghei sporozoites and monitored their behavior using intravital microscopy. Digital recordings show that sporozoites entering a liver lobule abruptly adhere to the sinusoidal cell layer, suggesting a high-affinity interaction. They glide along the sinusoid, with or against the bloodstream, to a Kupffer cell, and, by slowly pushing through a constriction, traverse across the space of Disse. Once inside the liver parenchyma, sporozoites move rapidly for many minutes, traversing several hepatocytes, until ultimately settling within a final one. Migration damage to hepatocytes was confirmed in liver sections, revealing clusters of necrotic hepatocytes adjacent to structurally intact, sporozoite-infected hepatocytes, and by elevated serum alanine aminotransferase activity. In summary, malaria sporozoites bind tightly to the sinusoidal cell layer, cross Kupffer cells, and leave behind a trail of dead hepatocytes when migrating to their final destination in the liver.
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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 | 0.001 |
| 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".