Evidence map›Paper›PMID 37423659›Full record

ArticleAnalytica chimica acta2023

Rapid diagnosis of COVID-19 using disposal paper capacitive sensor.

Partha P Sahu, Geetartha Sarma, Satyajit Das, Biswajyoti Borkakoty

Erratum issuedOpen access · greenAbstract read
In one paragraph

Article in Analytica chimica acta, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.3field-weighted citation impact, top 48% 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

0 citing papers in PubMed, 3 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors at 2 institutions in 1 country.

Partha P SahuDepartment of Electronics and Communication Engineering, Tezpur University, Napaam, Tezpur, 784028, Assam, India.
Geetartha SarmaDepartment of Electronics and Communication Engineering, Tezpur University, Napaam, Tezpur, 784028, Assam, India. Electronic address: geetarthasarma59@gmail.com.
Satyajit DasDepartment of Electronics and Communication Engineering, Tezpur University, Napaam, Tezpur, 784028, Assam, India.
Biswajyoti BorkakotyRegional VRDL, Regional Medical Research Centre, ICMR, N.E. Region, Dibrugarh, 786001, Assam, India.
Tezpur University · INRegional Medical Research Centre · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Accurate and rapid detection and isolation become indispensable to restrict the spread of COVID-19. Since the start of COVID-19 pandemic in December 2019, many indisposal diagnostic tools are being developed incessantly. Out of all presently used tools, the gold standard rRT- PCR tool having very high sensitivity and specificity is a time consuming complicated molecular technique having requirements of special expensive equipment. Here, the main focus of this work is to develop rapid disposal paper capacitance sensor having simple and easy detection. We discovered a strong interaction between limonin and Spike-glycoprotein of SARS-COV-2 in comparison to its interaction with other similar viruses such as HCOV-OC43, HCOV-NL63, HCOV-HKU1, Influenza B and A viruses. The antibody free capacitive sensor having comb electrode structure was fabricated on whatman paper with drop coating of limonin (extracted using green method from pomelo seeds) and calibrated with known swab samples. The Blind test with unknown swab samples shows high sensitivity of 91.5% and high specificity of 88.37%. Requiring low sample volume and detection time and using biodegradable materials in the sensor fabrication assure the potential application as a point of care disposal diagnostic tool.

Indexed as

COVID-19LimoninsCOVID-19 TestingHumansPandemicsSARS-CoV-2limoninLimonins

Identifiers

PMID37423659
PMCPMC10243487
OpenAlexW4379518682

What OpenQuestion holds

Textmetadata
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.