Differential Effector Pathways Regulate Memory CD8 T Cell Immunity against <i>Plasmodium berghei</i> versus <i>P</i> . <i>yoelii</i> Sporozoites
Bibliographic record
Abstract
Malaria results in >1,000,000 deaths per year worldwide. Although no licensed vaccine exists, much effort is currently focused on subunit vaccines that elicit CD8 T cell responses directed against Plasmodium parasite liver stage Ags. Multiple immune-effector molecules play a role in antimicrobial immunity mediated by memory CD8 T cells, including IFN-gamma, perforin, TRAIL, Fas ligand, and TNF-alpha. However, it is not known which pathways are required for memory CD8 T cell-mediated immunity against liver stage Plasmodium infection. In this study, we used a novel immunization strategy to generate memory CD8 T cells in the BALB/c mouse model of P. berghei or P. yoelii sporozoite infection to examine the role of immune-effector molecules in resistance to the liver stage infection. Our studies reveal that endogenous memory CD8 T cell-mediated protection against both parasite species is, in part, dependent on IFN-gamma, whereas perforin was only critical in protection against P. yoelii. We further show that neutralization of TNF-alpha in immunized mice markedly reduces memory CD8 T cell-mediated protection against both parasite species. Thus, our studies identify IFN-gamma and TNF-alpha as important components of the noncytolytic pathways that underlie memory CD8 T cell-mediated immunity against liver stage Plasmodium infection. Our studies also show that the effector pathways that memory CD8 T cells use to eliminate liver stage infection are, in part, Plasmodium species specific.
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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".