Evidence map›Paper›PMID 36505416›Full record

ReviewFrontiers in immunology2022

Profiling the B cell immune response elicited by vaccination against the respiratory virus SARS-CoV-2.

Elena Pettini, Donata Medaglini, Annalisa Ciabattini

Abstract readReview
In one paragraph

Review in Frontiers in immunology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

11 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Article
  6. Serum antibody screening using glycan arrays.Chemical Society reviews · 2024
    Review
  7. Isolation of Rare Antigen-Specific Memory B Cells via Antigen Tetramers.Methods in molecular biology (Clifton, N.J.) · 2024
    Article
  8. Article
  9. Review
  10. Article
  11. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Elena PettiniLaboratory of Molecular Microbiology and Biotechnology, Department of Medical Biotechnologies, University of Siena, Siena, Italy.
Donata MedagliniLaboratory of Molecular Microbiology and Biotechnology, Department of Medical Biotechnologies, University of Siena, Siena, Italy.
Annalisa CiabattiniLaboratory of Molecular Microbiology and Biotechnology, Department of Medical Biotechnologies, University of Siena, Siena, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

B cells play a fundamental role in host defenses against viral infections. Profiling the B cell response elicited by SARS-CoV-2 vaccination, including the generation and persistence of antigen-specific memory B cells, is essential for improving the knowledge of vaccine immune responsiveness, beyond the antibody response. mRNA-based vaccines have shown to induce a robust class-switched memory B cell response that persists overtime and is boosted by further vaccine administration, suggesting that memory B cells are critical in driving a recall response upon re-exposure to SARS-CoV-2 antigens. Here, we focus on the role of the B cell response in the context of SARS-CoV-2 vaccination, offering an overview of the different technologies that can be used to identify spike-specific B cells, characterize their phenotype using machine learning approaches, measure their capacity to reactivate following antigen encounter, and tracking the maturation of the B cell receptor antigenic affinity.

Indexed as

COVID-19SARS-CoV-2COVID-19 VaccinesHumansImmunityVaccinationCOVID-19 VaccinesB cell ELISpotBCR repertoirecomputational flow cytometryCOVID-19 vaccinesmemory B cellsrespiratory virusSARS-CoV-2

Identifiers

PMID36505416
PMCPMC9729280

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.