Evidence map›Paper›PMID 36196115›Full record

ReviewNational science review2022

Nanotechnology for the management of COVID-19 during the pandemic and in the post-pandemic era.

Chun Xu, Chang Lei, Sepanta Hosseinpour, Saso Ivanovski, Laurence J Walsh, Ali Khademhosseini

Open access · goldAbstract readReview
In one paragraph

Review in National science review, 2022. 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
3.1field-weighted citation impact, top 7% 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

6 citing papers in PubMed, 33 citations in OpenAlex.

  1. Article
  2. Navigating theNanoscale advances · 2026
    Review
  3. Review
  4. Review
  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

6 authors at 2 institutions in 2 countries.

Chun XuSchool of Dentistry, The University of Queensland, Brisbane 4006, Australia.ORCID https://orcid.org/0000-0001-8831-3607
Chang LeiAustralian Institute for Bioengineering and Nanotechnology, The University of Queensland, St Lucia 4072, Australia.
Sepanta HosseinpourSchool of Dentistry, The University of Queensland, Brisbane 4006, Australia.
Saso IvanovskiSchool of Dentistry, The University of Queensland, Brisbane 4006, Australia.
Laurence J WalshSchool of Dentistry, The University of Queensland, Brisbane 4006, Australia.
Ali KhademhosseiniTerasaki Institute for Biomedical Innovation, Los Angeles, CA 90064, USA.
The University of Queensland · AUTerasaki Foundation · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Following the global COVID-19 pandemic, nanotechnology has been at the forefront of research efforts and enables the fast development of diagnostic tools, vaccines and antiviral treatment for this novel virus (SARS-CoV-2). In this review, we first summarize nanotechnology with regard to the detection of SARS-CoV-2, including nanoparticle-based techniques such as rapid antigen testing, and nanopore-based sequencing and sensing techniques. Then we investigate nanotechnology as it applies to the development of COVID-19 vaccines and anti-SARS-CoV-2 nanomaterials. We also highlight nanotechnology for the post-pandemic era, by providing tools for the battle with SARS-CoV-2 variants and for enhancing the global distribution of vaccines. Nanotechnology not only contributes to the management of the ongoing COVID-19 pandemic but also provides platforms for the prevention, rapid diagnosis, vaccines and antiviral drugs of possible future virus outbreaks.

Indexed as

COVID-19diagnosisnanotechnologySARS-CoV-2vaccines

Identifiers

PMID36196115
PMCPMC9522393
OpenAlexW4283575972

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.