A simple and safe antibody neutralization assay based on polio pseudoviruses
Bibliographic record
Abstract
The evaluation of the immunogenicity of Sabin strain based Inactivated Poliovirus Vaccines (sIPV) necessitates the use of wild strains in neutralization assays to assess the potential cross-reactivity of antibodies. The live virus strains including wild and Sabin strains must be handled in level 3 biocontainment laboratories. To develop an alternative assay without the use of a live virus, we constructed Mahoney, MEF-1, and Saukett pseudovirions by inserting luciferase reporter genes into intact capsid proteins. Afterward, we developed a pseudovirus-based neutralization test (pNT) and evaluated for the specificity and reproducibility. We tested serum samples from a clinical trial on sIPV vaccines by pNT and compared the results with those obtained from conventional neutralization tests (cNT). A strong correlation was observed between two methods, with the correlation coefficients of all three types of IPV vaccines being greater than 0.82 (p < 0.0001). The Geometric Mean Titer (GMT) values obtained by pNT were approximately four times higher than that by cNT, revealing the better sensitivity of pNT. In conclusion, pNT is a safe, rapid and sensitive quantitative assay with the potential of being an alternative for the evaluation of the potency of polio 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".