Evidence map›Paper›PMID 32849655›Full record

ArticleFrontiers in immunology2020

Combating COVID-19: MVA Vector Vaccines Applied to the Respiratory Tract as Promising Approach Toward Protective Immunity in the Lung.

Reinhold Förster, Henrike Fleige, Gerd Sutter

Open access · goldAbstract read
In one paragraph

Article in Frontiers in immunology, 2020. 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
0.4field-weighted citation impact, top 25% 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

11 citing papers in PubMed, 15 citations in OpenAlex.

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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 2 institutions in 1 country.

Reinhold FörsterInstitute of Immunology, Hannover Medical School, Hanover, Germany.
Henrike FleigeInstitute of Immunology, Hannover Medical School, Hanover, Germany.
Gerd SutterDivision of Virology, Institute for Infectious Diseases and Zoonoses, Ludwig-Maximilians-Universität München, Munich, Germany.
Medizinische Hochschule Hannover · DEGerman Center for Infection Research · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The lung is the vital target organ of coronavirus disease 2019 (COVID-19) caused by infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). In the majority of patients the most active virus replication seems to be found in the upper respiratory tract, severe cases however suffer from SARS-like disease associated with virus replication in lung tissues. Due to the current lack of suitable anti-viral drugs the induction of protective immunity such as neutralizing antibodies in the lung is the key aim of the only alternative approach-the development and application of SARS-CoV-2 vaccines. However, past experience from experimental animals, livestock, and humans showed that induction of immunity in the lung is limited following application of vaccines at peripheral sides such as skin or muscles. Based on several considerations we therefore propose here to consider the application of a Modified Vaccinia virus Ankara (MVA)-based vaccine to mucosal surfaces of the respiratory tract as a favorable approach to combat COVID-19.

Indexed as

Administration, MucosalAnimalsAntibodies, NeutralizingAntibodies, ViralBetacoronavirusBronchiCoronavirus InfectionsCOVID-19HumansImmunoglobulin ALymphoid TissuePandemicsPlasma CellsPneumonia, ViralRespiratory MucosaSARS-CoV-2Antibodies, NeutralizingAntibodies, ViralImmunoglobulin ASpike Glycoprotein, Coronavirusspike protein, SARS-CoV-2Vaccines, AttenuatedViral VaccinesBALTCOVID-19lungMVASARS-CoV-2vaccine

Identifiers

PMID32849655
PMCPMC7426738
OpenAlexW3047823663

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.