Evidence map›Paper›PMID 37973637›Full record

ReviewArchives of virology2023

Impact of COVID-19 vaccination on saliva immune barriers: IgA, lysozyme, and lactoferrin.

Hanadi H Abdul-Kareem, Marwan Y Al-Maqtoofi, Ahmed A Burghal

Abstract readReview
PubMed Publisher
In one paragraph

Review in Archives of virology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.6field-weighted citation impact, top 17% of its field
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

4 citing papers in PubMed, 8 citations in OpenAlex.

  1. Article
  2. Review
  3. Review
  4. Article
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 at 1 institution in 1 country.

Hanadi H Abdul-KareemBiology Department, College of Science University of Basrah, Basrah, 61001, Iraq.
Marwan Y Al-MaqtoofiBiology Department, College of Science University of Basrah, Basrah, 61001, Iraq. marwan.almaqtoofi@uobasrah.edu.iq.ORCID http://orcid.org/0000-0001-6126-7874
Ahmed A BurghalBiology Department, College of Science University of Basrah, Basrah, 61001, Iraq.
University of Basrah · IQ

Funding

University of Basrah 2023
6 · The paper itself

Abstract

Understanding the role of salivary constituents, such as lactoferrin, lysozyme, and secretory immunoglobulin A (sIgA), in immune protection and defense mechanisms against microbial invasion and colonization of the airways is important in light of the ongoing severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic. The salivary immune barrier in individuals affected by COVID-19 may contribute to disease prognosis. Thus, the aim of the present review is to evaluate the effect of COVID-19 vaccines on the immunological composition of saliva. IgA antibodies generated by vaccination can neutralize the virus at mucosal surfaces, whereas antimicrobial peptides, such as lysozyme and lactoferrin, have broad-spectrum antimicrobial activity. Collectively, these components contribute to the protective immune response of the oral cavity and may help minimize viral transmission as well as the severity of COVID-19. Measuring the levels of these components in the saliva of COVID-19-vaccinated individuals can help in evaluating the vaccine's ability to induce mucosal immunity, and it might also provide insights into whether saliva can be used in diagnostics or surveillance for monitoring immune responses following vaccination. This also has implications for viral transmission.

Indexed as

COVID-19MuramidaseAntibodies, ViralCOVID-19 VaccinesHumansImmunoglobulin ALactoferrinSalivaSARS-CoV-2VaccinationAntibodies, ViralCOVID-19 VaccinesImmunoglobulin ALactoferrinMuramidase

Identifiers

PMID37973637
OpenAlexW4388719988

What OpenQuestion holds

Textmetadata
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.