ArticleScientific reports2023
Refinement of an ovine-based immunoglobulin therapy against SARS-CoV-2, with comparison of whole IgG versus F(ab')
Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 1 paper.
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
1 citing paper in PubMed.
- Hyperimmune Globulins in COVID-19.Current topics in microbiology and immunology · 2025Review
Corrections and comments
- Erratum issued
Authors and funding
24 authors.
Funding
Abstract
The development of new therapies against SARS-CoV-2 is required to extend the toolkit of intervention strategies to combat the global pandemic. In this study, hyperimmune plasma from sheep immunised with whole spike SARS-CoV-2 recombinant protein has been used to generate candidate products. In addition to purified IgG, we have refined candidate therapies by removing non-specific IgG via affinity binding along with fragmentation to eliminate the Fc region to create F(ab')
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Identifiers
What OpenQuestion holds
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.