Evidence map›Paper›PMID 33833758›Full record

ReviewFrontiers in immunology2021

Bovine Coronavirus Immune Milk Against COVID-19.

Antonio Arenas, Carmen Borge, Alfonso Carbonero, Ignacio Garcia-Bocanegra, David Cano-Terriza, Javier Caballero, Antonio Arenas-Montes

Abstract readReview
In one paragraph

Review in Frontiers in immunology, 2021. 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. Article
  2. Article
  3. Article
  4. Article
  5. Review
  6. Review
  7. Review
  8. Review
  9. Parainfluenza and corona viruses in a fallow deer (Frontiers in veterinary science · 2022
    Article
  10. Article
  11. 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

7 authors.

Antonio ArenasDepartment of Animal Health, University of Cordoba, Córdoba, Spain.
Carmen BorgeDepartment of Animal Health, University of Cordoba, Córdoba, Spain.
Alfonso CarboneroDepartment of Animal Health, University of Cordoba, Córdoba, Spain.
Ignacio Garcia-BocanegraDepartment of Animal Health, University of Cordoba, Córdoba, Spain.
David Cano-TerrizaDepartment of Animal Health, University of Cordoba, Córdoba, Spain.
Javier CaballeroDepartment of Animal Health, University of Cordoba, Córdoba, Spain.
Antonio Arenas-MontesDepartment of Animal Health, University of Cordoba, Córdoba, Spain.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

After a year of evolution of the SARS-CoV-2 epidemic, there is still no specific effective treatment for the disease. Although the majority of infected people experience mild disease, some patients develop a serious disease, especially when other pathologies concur. For this reason, it would be very convenient to find pharmacological and immunological mechanisms that help control SARS-CoV-2 infection. Since the COVID-19 and BCoV viruses are very close phylogenetically, different studies demonstrate the existence of cross-immunity as they retain shared epitopes in their structure. As a possible control measure against COVID-19, we propose the use of cow's milk immune to BCoV. Thus, the antigenic recognition of some highly conserved structures of viral proteins, particularly M and S2, by anti-BCoV antibodies present in milk would cause a total or partial inactivation of SARS-COV-2 (acting as a particular vaccine) and be addressed more easily by GALT's highly specialized antigen-presenting cells, thus helping the specific immune response.

Indexed as

AnimalsAntibodies, ViralCattleCoronavirus, BovineCOVID-19SARS-CoV-2Antibodies, ViralBCoVcontrolCOVID-19immune milkSARS-CoV-2

Identifiers

PMID33833758
PMCPMC8021920

What OpenQuestion holds

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LicenceCC BY
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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.