Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 395

The DOI matches its Crossref record; 12 of the 12 references it cites were found in a registry or an index.

T-cell immunity of SARS-CoV: Implications for vaccine development against MERS-CoV

Open access
Liu, William J., Zhao, Min, Liu, Kefang, Xu, Kun, Wong, Gary, Tan, Wenjie, Gao, George F.·2017·Antiviral Research

Abstract

Over 12 years have elapsed since severe acute respiratory syndrome (SARS) triggered the first global alert for coronavirus infections. Virus transmission in humans was quickly halted by public health measures and human infections of SARS coronavirus (SARS-CoV) have not been observed since. However, other coronaviruses still pose a continuous threat to human health, as exemplified by the recent emergence of Middle East respiratory syndrome (MERS) in humans. The work on SARS-CoV widens our knowledge on the epidemiology, pathophysiology and immunology of coronaviruses and may shed light on MERS coronavirus (MERS-CoV). It has been confirmed that T-cell immunity plays an important role in recovery from SARS-CoV infection. Herein, we summarize T-cell immunological studies of SARS-CoV and discuss the potential cross-reactivity of the SARS-CoV-specific immunity against MERS-CoV, which may provide useful recommendations for the development of broad-spectrum vaccines against coronavirus infections.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1016/j.antiviral.2016.11.006

Cites

12 of 12 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 12 references

Cited by

See all 395

Metadata

Authors
Liu, W. J., Zhao, M., Liu, K., Xu, K., Wong, G., Tan, W., & Gao, G. F.
Venue
Antiviral Research
Publisher
Elsevier BV
Published
2017-01
Volume
137
Pages
82-92
ISSN
0166-3542 (ISSN-L)
OpenAlex
W2555838982
Cited by
395
References
12
FWCI
3.92
Type
journal article
Language
en
Open access
green

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: T-cell immunity of SARS-CoV: Implications for vaccine development against MERS-CoV. https://app.cochat.ai/papers/10.1016/j.antiviral.2016.11.006
The paper
Liu, W. J., Zhao, M., Liu, K., Xu, K., Wong, G., Tan, W., & Gao, G. F. (2017). T-cell immunity of SARS-CoV: Implications for vaccine development against MERS-CoV. Antiviral Research. https://doi.org/10.1016/j.antiviral.2016.11.006

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.