Evidence map›Paper›PMID 41271759›Full record

ArticleNPJ vaccines2025

Immunogenicity and efficacy of homologous and heterologous NDV and MVA SARS-CoV-2 vaccines in mice and hamsters.

Patricia Pérez, Kaijun Jiang, Irene González-Domínguez, Daniel Rodríguez-Martín, Adam Abdeljawad, Anastasija Cupic, Stefan Slamanig, Sara Flores, María A Noriega, Pedro J Sánchez-Cordón and 6 more

Abstract read
In one paragraph

Article in NPJ vaccines, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

16 authors.

Patricia Pérez *Department of Molecular and Cellular Biology, Centro Nacional de Biotecnología (CNB), Consejo Superior de Investigaciones Científicas (CSIC), Madrid, Spain.
Kaijun Jiang *Department of Microbiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Irene González-DomínguezDepartment of Microbiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Daniel Rodríguez-MartínDepartment of Molecular and Cellular Biology, Centro Nacional de Biotecnología (CNB), Consejo Superior de Investigaciones Científicas (CSIC), Madrid, Spain.
Adam AbdeljawadDepartment of Microbiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Anastasija CupicDepartment of Microbiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Stefan SlamanigDepartment of Microbiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Sara FloresDepartment of Molecular and Cellular Biology, Centro Nacional de Biotecnología (CNB), Consejo Superior de Investigaciones Científicas (CSIC), Madrid, Spain.
María A NoriegaDepartment of Molecular and Cellular Biology, Centro Nacional de Biotecnología (CNB), Consejo Superior de Investigaciones Científicas (CSIC), Madrid, Spain.
Pedro J Sánchez-CordónPathology Department, Centro de Investigación en Sanidad Animal (CISA), Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria (INIA), Consejo Superior de Investigaciones Científicas (CSIC), Valdeolmos, Madrid, Spain.
Nicholas LemusDepartment of Microbiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Tsoi Ying LaiDepartment of Microbiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Weina SunDepartment of Microbiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Mariano EstebanDepartment of Molecular and Cellular Biology, Centro Nacional de Biotecnología (CNB), Consejo Superior de Investigaciones Científicas (CSIC), Madrid, Spain.
Adolfo García-SastreDepartment of Microbiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA. Adolfo.Garcia-Sastre@mssm.edu.
Juan García-ArriazaDepartment of Molecular and Cellular Biology, Centro Nacional de Biotecnología (CNB), Consejo Superior de Investigaciones Científicas (CSIC), Madrid, Spain. jfgarcia@cnb.csic.es.

Funding

NIAID Centers of Excellence for Influenza Research and Response: Universal Influenza Vaccine Research Activities75N93021C00014 · NIAID · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI GARCIA-SASTRE, ADOLFO · 2021 to 2025
$62.6M
TRAINING PROGRAM: MECHANISMS OF VIRUS-HOST INTERACTIONST32AI007647 · NIAID · MOUNT SINAI SCHOOL OF MEDICINE OF NYU · PI Domenico Tortorella · 2000 to 2026
$11.5M
CSIC grant 2020E84CSIC grant 202120E079NIAID NIH HHS 75N93021C00014NIAID NIH HHS T32 AI007647Spanish MCIU/AEI/10.13039/501100011033 grant PID2020-114481RB-I00Spanish Ministry of Science, Innovation and Universities (MCIU)/Spanish Research Agency (AEI)/10.13039/501100011033 CNS2022-135511
6 · The paper itself

Abstract

Effective vaccination strategies adaptable to emerging viruses like SARS-CoV-2 and capable of inducing robust protective immunity are needed. We evaluated the immunogenicity and protective efficacy of homologous and heterologous prime/boost regimens against SARS-CoV-2 in K18-hACE2 mice and Syrian hamsters using Newcastle disease virus (NDV-HXP-S, intranasal) and modified vaccinia virus Ankara (MVA-S(3P), intramuscular) vectors encoding a prefusion-stabilized SARS-CoV-2 spike (S) protein. All regimens protected against weight loss and markedly reduced viral replication and lung pathology. Vaccination induced serum anti-S and anti-receptor binding domain IgGs and neutralizing antibodies against ancestral virus and variants. In mice, mucosal anti-S IgA and IgG were detected after NDV-HXP-S immunization. Homologous MVA-S(3P)/MVA-S(3P) and heterologous NDV-HXP-S/MVA-S(3P) elicited higher polyfunctional systemic T-cell responses, while homologous NDV-HXP-S/NDV-HXP-S induced stronger pulmonary CD8

Identifiers

PMID41271759
PMCPMC12638851

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.