Evidence map›Paper›PMID 36978782›Full record

ArticleBioengineering (Basel, Switzerland)2023

Label-Free Saliva Test for Rapid Detection of Coronavirus Using Nanosensor-Enabled SERS.

Swarna Ganesh, Ashok Kumar Dhinakaran, Priyatha Premnath, Krishnan Venkatakrishnan, Bo Tan

Open access · goldFull text read
In one paragraph

Article in Bioengineering (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.4field-weighted citation impact, top 21% 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

4 citing papers in PubMed, 7 citations in OpenAlex.

  1. Review
  2. Review
  3. Review
  4. 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

5 authors at 2 institutions in 2 countries.

Swarna GaneshKeenan Research Center for Biomedical Science, Unity Health Toronto, Toronto, ON M5B 1W8, Canada.
Ashok Kumar DhinakaranKeenan Research Center for Biomedical Science, Unity Health Toronto, Toronto, ON M5B 1W8, Canada.
Priyatha PremnathDepartment of biomedical engineering, College of Engineering and Applied Sciences, University of Wisconsin, Milwaukee, WI 53211, USA.
Krishnan VenkatakrishnanKeenan Research Center for Biomedical Science, Unity Health Toronto, Toronto, ON M5B 1W8, Canada.
Bo TanKeenan Research Center for Biomedical Science, Unity Health Toronto, Toronto, ON M5B 1W8, Canada.ORCID 0000-0001-8141-4819
St. Michael's Hospital · CAUniversity of Wisconsin–Milwaukee · US

Funding

Natural Sciences and Engineering Research Council 132950, 134361
6 · The paper itself

Abstract

The recent COVID-19 pandemic has highlighted the inadequacies of existing diagnostic techniques and the need for rapid and accurate diagnostic systems. Although molecular tests such as RT-PCR are the gold standard, they cannot be employed as point-of-care testing systems. Hence, a rapid, noninvasive diagnostic technique such as Surface-enhanced Raman scattering (SERS) is a promising analytical technique for rapid molecular or viral diagnosis. Here, we have designed a SERS- based test to rapidly diagnose SARS-CoV-2 from saliva. Physical methods synthesized the nanostructured sensor. It significantly increased the detection specificity and sensitivity by ~ten copies/mL of viral RNA (~femtomolar concentration of nucleic acids). Our technique combines the multiplexing capability of SERS with the sensitivity of novel nanostructures to detect whole virus particles and infection-associated antibodies. We have demonstrated the feasibility of the test with saliva samples from individuals who tested positive for SARS-CoV-2 with a specificity of 95%. The SERS-based test provides a promising breakthrough in detecting potential mutations that may come up with time while also preparing the world to deal with other pandemics in the future with rapid response and very accurate results.

Indexed as

coronavirusCOVID-19nanosensorsSERS

Identifiers

PMID36978782
PMCPMC10045265
OpenAlexW4353062165

What OpenQuestion holds

Textfull text, public
LicenceCC BY
measurements read15
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.