ArticlePloS one2024
Absolute concentration estimation of COVID-19 convalescent and post-vaccination IgG antibodies.
Article in PloS one, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
6 citing papers in PubMed.
- BCG-Induced DNA Methylation Changes Improve Coronavirus Disease 2019 Vaccine Immunity Without Decreasing the Risk for Severe Acute Respiratory Syndrome Coronavirus 2 Infection.Open forum infectious diseases · 2025Trial
- ACE2-like Catalytic Activity in Anti-SARS-CoV-2 Spike Protein Monoclonal Antibodies.Pathogens (Basel, Switzerland) · 2026Article
- A T7 RNAP regulatory toolbox for cell-free network engineering and biosensing applications.Nature communications · 2026Article
- Article
- COVID-19 convalescent plasma safety and efficacy analysis for biologics license application approval.Expert review of anti-infective therapy · 2026Review
- Identification of broadly inhibitory anti-PfEMP1 antibodies by mass spectrometry sequencing of plasma IgG from a malaria-exposed child.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
14 authors.
Funding
Abstract
Soon after commencement of the SARS-CoV-2 disease outbreak of 2019 (COVID-19), it became evident that the receptor-binding domain of the viral spike protein is the target of neutralizing antibodies that comprise a critical element of protective immunity to the virus. This study addresses the relative lack of information regarding actual antibody concentrations and binding affinities in convalescent plasma (CP) samples from COVID-19 patients and extends these analyses to post-vaccination (PV) samples to estimate protective IgG antibody (Ab) levels. A direct enzyme-linked immunosorbent assay (ELISA) was used to measure IgG anti-spike protein (SP) antibodies (Abs) relative to human chimeric spike S1 Ab standards. Microplate wells were coated with recombinant SP. Affinities of Ab binding to SP were determined by previously described methods. Binding affinities were also determined in an RBD-specific sandwich ELISA. Two indices of protective immunity were determined as permutations of Ab molar concentration divided by affinity as dissociation constant (KD). The range and geometric means of Ab concentrations in 21 CP and 21 PV samples were similar and a protective Ab level of 7.5 μg/ml was determined for the latter population, based on 95% of the normal distribution of the PV population. A population (n = 21) of plasma samples from individuals receiving only one vaccination with the BNT162b2 or mRNA-1273 vaccines (PtV) exhibited a geometric mean Ab concentration significantly (p < 0.03) lower than the PV population. The results of this study have implications for future vaccine development, projection of protective efficacy duration, and understanding of the immune response to SARS-CoV-2 infection.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.