A safe and reliable neutralization assay based on pseudovirus to measure neutralizing antibody titer against poliovirus
Bibliographic record
Abstract
With the promotion of inactivated poliomyelitis vaccine (IPV) and live attenuated oral poliomyelitis vaccine (OPV), the global reported cases of poliomyelitis have reduced sharply from 0.35 million in 1988 to 74 in 2015. The Polio Eradication & Endgame Strategic Plan published by WHO in 2013 included the strategy of implementation of poliovirus safe handling and containment measures to minimize the risks of facility-associated reintroduction of virus into the polio-free community to prevent the re-import of poliovirus. Toward this strategy, we produced replication-incompetent pseudovirus of poliovirus type 1, 2, 3 attenuated strains by constructing poliovirus capsid expression vectors and poliovirus replicon then transfecting HEK293T cells and developed a pseudovirus-based neutralization assay (pNA) to determine neutralizing antibody titer which is more secure, time-saving and reliable than conventional neutralization assay (cNA). By using anti-poliovirus rat serum, we demonstrated excellent correlation between neutralizing antibody titers measured by cNA and pNA. It was concluded that pNA can be a potential alternative to replace cNA as a safe and time-saving system for titer determination after live poliovirus's safekeeping.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 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 | 0.001 |
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".