Flow cytometry: An efficient method for antigenicity measurement and particle characterization on an adjuvanted vaccine candidate H4-IC31 for tuberculosis
Bibliographic record
Abstract
We have developed an accurate, precise and stability-indicating flow cytometry (FC) based assay to directly measure antigenicity of H4 protein (also known as HyVac4) in a vaccine formulation of H4-IC31, without desorbing the H4 protein from the IC31 adjuvant. This method involves immuno-staining of H4-IC31 complex with anti-H4 monoclonal antibodies (mAbs) followed by FC analysis. The assay is not only able to consistently measure H4 antigenicity levels in H4-IC31 stored under normal condition at 2-8°C, but also able to detect changes in H4 antigenicity after H4-IC31 undergoes heat stress or freeze-thawing. In addition, the FC method is able to characterize particle morphology while measuring antigenicity. The biological relevance of the changes in H4 antigenicity detected by the FC assay was supported by an in vitro cell based functional assay using human PBMCs to measure IFN-gamma (IFN-γ) secretion upon re-stimulation with H4-IC31. Our results show that the FC based antigenicity assay can efficiently monitor the biological and physicochemical properties of H4-IC31 and is an indicator for adjuvanted vaccine product stability.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".