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Record W2766313725 · doi:10.1016/j.jim.2017.10.005

Flow cytometry: An efficient method for antigenicity measurement and particle characterization on an adjuvanted vaccine candidate H4-IC31 for tuberculosis

2017· article· en· W2766313725 on OpenAlexaff
Liwei He, Jin Su, Marin Ming, Lídice Bernardo, Tricia Chen, Lucy Gisonni-Lex, Beata Gajewska

Bibliographic record

VenueJournal of Immunological Methods · 2017
Typearticle
Languageen
FieldMedicine
TopicTuberculosis Research and Epidemiology
Canadian institutionsSanofi (Canada)
Fundersnot available
KeywordsAntigenicityFlow cytometryTuberculosisVirologyMicrobiologyMedicineImmunologyBiologyAntigenPathology

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.013
metaresearch head score (Gemma)0.016
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.664
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0130.016
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.115
GPT teacher head0.471
Teacher spread0.356 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations7
Published2017
Admission routes1
Has abstractyes

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