Evidence map›Paper›PMID 33912161›Full record

ReviewFrontiers in immunology2021

Virus Caused Imbalance of Type I IFN Responses and Inflammation in COVID-19.

Jintao Zhang, Chunyuan Zhao, Wei Zhao

Open access · goldAbstract 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 25 papers.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed
2.0field-weighted citation impact, top 11% 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

25 citing papers in PubMed, 37 citations in OpenAlex.

  1. Viral Prognosis Using Proteomics.Advances in experimental medicine and biology · 2026
    Review
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  6. Antioxidants (Basel, Switzerland) · 2025
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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.

Jintao ZhangDepartment of Immunology, School of Basic Medical Science, Cheeloo College of Medicine, Shandong University, Jinan, China.
Chunyuan ZhaoDepartment of Immunology, School of Basic Medical Science, Cheeloo College of Medicine, Shandong University, Jinan, China.
Wei ZhaoDepartment of Immunology, School of Basic Medical Science, Cheeloo College of Medicine, Shandong University, Jinan, China.
Shandong University · CNState Key Laboratory of Microbial Technology

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The global expansion of coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has emerged as one of the greatest public health challenges and imposes a great threat to human health. Innate immunity plays vital roles in eliminating viruses through initiating type I interferons (IFNs)-dependent antiviral responses and inducing inflammation. Therefore, optimal activation of innate immunity and balanced type I IFN responses and inflammation are beneficial for efficient elimination of invading viruses. However, SARS-CoV-2 manipulates the host's innate immune system by multiple mechanisms, leading to aberrant type I IFN responses and excessive inflammation. In this review, we will emphasize the recent advances in the understanding of the crosstalk between host innate immunity and SARS-CoV-2 to explain the imbalance between inflammation and type I IFN responses caused by viral infection, and explore potential therapeutic targets for COVID-19.

Indexed as

COVID-19COVID-19 Drug TreatmentHost-Pathogen InteractionsHumansImmunity, InnateInflammationInterferon Type ILungSARS-CoV-2Signal TransductionViral ProteinsInterferon Type IViral ProteinsCOVID-19inflammationinnate immunitySARS-CoV-2type I interferons

Identifiers

PMID33912161
PMCPMC8071932
OpenAlexW3153204333

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.