Influenza Virus-Like Particles Presenting both Toxoplasma gondii ROP4 and ROP13 Enhance Protection against T. gondii Infection
Bibliographic record
Abstract
Rhoptry organelle proteins (ROPs) secreted by Toxoplasma gondii (T. gondii) play a critical role during parasite invasion into host cells. In this study, virus-like particles (VLPs) vaccines containing ROP4 and/or ROP13 together with influenza M1 were generated. ROP4+ROP13 VLPs were produced by combining ROP4 VLPs with ROP13 VLPs, and ROP(4 + 13) VLPs by co-infecting insect cells with recombinant baculovirus expressing ROP4 or ROP13. Mice intranasally immunized with ROP(4 + 13) VLPs showed significantly higher levels of IgG, IgG1, IgG2a and IgA antibody responses in sera compared to ROP4+ROP13VLPs. Upon challenge infection by oral route, mice immunized with ROP(4 + 13) VLPs elicited higher levels of IgG and IgA antibody responses in fecal, urine, intestine and vaginal samples as well as CD4+ T, CD8+ T cells, and germinal center B cell responses compared to other type of vaccines, ROP4 VLPs, ROP13 VLPs, and ROP4+ROP13 VLPs. ROP(4 + 13) VLPs vaccination showed a significant decrease in the size and number of cyst in the brain and less body weight loss compared to combination ROP4+ROP13 VLPs upon challenge infection with T. gondii ME49. These results indicated that the ROP(4 + 13) VLPs vaccination provided enhanced protection against T. gondii infection compared to ROP4+ROP13 VLPs, providing an important insight into vaccine design strategy for T. gondii VLPs vaccines.
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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".