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Record W4284896907 · doi:10.1002/jmv.27983

Immunoassay and mass cytometry revealed immunological profiles induced by inactivated BBIBP COVID‐19 vaccine

2022· article· en· W4284896907 on OpenAlexaff
Zhangkai J. Cheng, Huimin Huang, Qiwen Liu, Ruifen Zhong, Zhiman Liang, Mingshan Xue, Mingtao Liu, Siping Li, Hongman Wang, Peiyan Zheng, Chunfu Zheng, Baoqing Sun

Bibliographic record

VenueJournal of Medical Virology · 2022
Typearticle
Languageen
FieldMedicine
TopicSARS-CoV-2 and COVID-19 Research
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsAntibodyMedicineBooster doseVirologyImmunologyVaccinationTiterNeutralizing antibodyImmune systemPotencyImmunoassayBooster (rocketry)VirusCoronavirus disease 2019 (COVID-19)BiologyInternal medicineIn vitroInfectious disease (medical specialty)

Abstract

fetched live from OpenAlex

With the global prevalence of COVID-19 and the constant emergence of viral variants, boosters for COVID-19 vaccines to enhance antibody titers in human bodies will become an inevitable trend. However, there is a lack of data on antibody levels and the protective effects of booster injections. This study monitored and analyzed the antibody potency and the antibody responses induced by the booster injection in the subjects who received three vaccine doses. The study was conducted in a multicenter collaboration and recruited 360 healthy adults aged 20-74. Participants received the first, second, and booster doses of inactivated Sinopharm/BBIBP COVID-19 vaccine at 0, 1, and 7 months. Vaccine-induced virus-specific antibody levels (SARS-COV-2-IgA/IgM/IgG) were monitored at multiple time points, surrogate virus neutralization test (sVNT), and the spatial distribution and proportion of immune cells and markers were analyzed using the CyTOF method before vaccination and a month after the second dose. The titers of SARS-CoV-2-IgA/IgM/IgG and neutralizing antibodies increased to a high level in the first month after receiving the second dose of vaccine and declined slowly after that. The antibody levels of SARS-CoV-2-IgG and sVNT were significantly increased at 0.5 months after the induction of the booster (p < 0.05). Despite a downward trend, the antibody levels were still high in the following 6 months. The B cell concentration (in humoral sample) a month after the second injection was significantly reduced compared to that before the vaccine injection (p < 0.05). The proportion of the C01 cell cluster was significantly decreased compared with that before vaccine injection (p < 0.05). Individual cell surface markers showed distinctions in spatial distribution but were not significantly different. This study has shown that serum antibody titer levels will decrease with time by monitoring and analyzing the antibody efficacy and the antibody reaction caused by the booster injection of healthy people who received the whole vaccination (completed three injections). Still, the significant peak of the antibody titer levels after booster highlights the recall immune response. It can maintain a high concentration of antibody levels for a long time, which signifies that the protection ability has been enhanced following the injection of booster immunization. Additionally, CyTOF data shows the active production of antibodies and the change in the immunity environment.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

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.

Opus teacher head0.038
GPT teacher head0.366
Teacher spread0.328 · 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

Citations7
Published2022
Admission routes1
Has abstractyes

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