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Selection of Sorbent for Poliovirus Vaccine Strain Concentrate Purification by Gel Filtration

2021· article· en· W4205313400 on OpenAlexaff
Anastasia A. Kovpak, Yury Ivin, Аnna A. Shishova, Alexei Sorokin, Maria A Prostova, A. V. Belyakova, А. А. Синюгина, Aydar A. Ishmukhametov, Y.H. Hapchaev, Anatoly P. Gmyl

Bibliographic record

VenueBiotekhnologiya · 2021
Typearticle
Languageen
FieldMedicine
TopicViral Infections and Immunology Research
Canadian institutionsUniversity of Lethbridge
Fundersnot available
KeywordsPoliovirusVirologyFiltration (mathematics)ChromatographySize-exclusion chromatographyChemistryVirusMicrobiologyBiologyEnzymeBiochemistry

Abstract

fetched live from OpenAlex

In the production of anti-virus vaccines, the replacement of wild-type with attenuated strains is becoming relevant. Sabin strains are the most suitable candidates for this replacement in the production of inactivated poliovirus vaccines. The main problem in the development of methods for purification of viral particles of Sabin strains is the preservation of their stability and antigenic properties. We have compared the sorbents used for gel-filtration of poliovirus concentrates and have selected a chromatographic resin, Sephacryl S-300HR, which provides a high yield of the target product and its high purity both during cultivation in roller bottles and in bioreactors. It was also shown that, along with effective purification, Sephacryl S-300HR allows preservation of the polyovirus antigenic properties and can be used in the preparation of monovalent inactivated poliovirus concentrates that meet the good quality requirements. inactivated polio vaccine (IPV), oral polio vaccine (OPV), poliomyelitis, chromatographic purification, gel filtration The authors grateful to L.P. Antonova and A.A. Butusova for their assistance in conducting the research.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.002

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 head0.032
GPT teacher head0.327
Teacher spread0.295 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations4
Published2021
Admission routes1
Has abstractyes

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