Evidence map›Paper›PMID 40872762›Full record

ReviewViruses2025

The Role of SARS-CoV-2 Nucleocapsid Protein in Host Inflammation.

Yujia Cao, Yaju Wang, Dejian Huang, Yee-Joo Tan

Abstract readReview
In one paragraph

Review in Viruses, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
  2. Article
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  4. Article
  5. Review
  6. 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

4 authors.

Yujia CaoDepartment of Food Science and Technology, National University of Singapore, Singapore 117542, Singapore.ORCID 0000-0001-9984-3080
Yaju WangInfectious Diseases Translational Research Programme, Department of Microbiology and Immunology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117545, Singapore.
Dejian HuangDepartment of Food Science and Technology, National University of Singapore, Singapore 117542, Singapore.ORCID 0000-0002-2305-3960
Yee-Joo TanInfectious Diseases Translational Research Programme, Department of Microbiology and Immunology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117545, Singapore.ORCID 0000-0002-2278-4497

Funding

Ministry of Education T2EP30121-0012
6 · The paper itself

Abstract

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of coronavirus disease 2019 (COVID-19), has posed substantial health threats and triggered widespread global economic disruption. The nucleocapsid (N) protein of SARS-CoV-2 is not only a key structural protein but also instrumental in mediating the host immune response, contributing significantly to inflammation and viral pathogenesis. Due to its immunogenic properties, SARS-CoV-2 N protein also interacts with host factors associated with various pre-existing inflammatory conditions and may possibly contribute to the long-term symptoms suffered by some COVID-19 patients after recovery-known as long COVID. This review provides a comprehensive overview of recent advances in elucidating the biological functions of the N protein. In particular, it highlights the mechanisms by which the N protein contributes to host inflammatory responses and elaborates on its association with long COVID and pre-existing inflammatory disorders.

Indexed as

Coronavirus Nucleocapsid ProteinsCOVID-19InflammationPhosphoproteinsSARS-CoV-2AnimalsHost-Pathogen InteractionsHumansCoronavirus Nucleocapsid Proteinsnucleocapsid phosphoprotein, SARS-CoV-2Phosphoproteinsbiological functionhost inflammationlong COVIDnucleocapsid proteinSARS-CoV-2

Identifiers

PMID40872762
PMCPMC12390639

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.