Long-term cellular immunity of vaccines for Zaire Ebola Virus Diseases
Bibliographic record
Abstract
Recent Ebola outbreaks underscore the importance of continuous prevention and disease control efforts. Authorized vaccines include Merck’s Ervebo (rVSV-ZEBOV) and Johnson & Johnson’s two-dose combination (Ad26.ZEBOV/MVA-BN-Filo). Here, in a five-year follow-up of the PREVAC randomized trial (NCT02876328), we report the results of the immunology ancillary study of the trial. The primary endpoint is to evaluate long-term memory T-cell responses induced by three vaccine regimens: Ad26–MVA, rVSV, and rVSV–booster. Polyfunctional EBOV-specific CD4+ T-cell responses increase after Ad26 priming and are further boosted by MVA, whereas minimal responses are observed in the rVSV groups, declining after one year. In-vitro expansion for eight days show sustained EBOV-specific T-cell responses for up to 60 months post-prime vaccination with both Ad26-MVA and rVSV, with no decline. Cytokine production analysis identify shared biomarkers between the Ad26-MVA and rVSV groups. In secondary endpoint, we observed an elevation of pro-inflammatory cytokines at Day 7 in the rVSV group. Finally, we establish a correlation between EBOV-specific T-cell responses and anti-EBOV IgG responses. Our findings can guide booster vaccination recommendations and help identify populations likely to benefit from revaccination. In this immunological ancillary study of the PREVAC trial, the authors show that approved Ebola virus vaccines induce memory T-cell responses that persist during the five year follow-up after initial vaccination.
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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 | 0.001 | 0.001 |
| 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) | 0.002 | 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".