Evidence map›Paper›PMID 35728365›Full record

ArticleBiosensors & bioelectronics2022

A compact, low-cost, and binary sensing (BiSense) platform for noise-free and self-validated impedimetric detection of COVID-19 infected patients.

Razieh Salahandish, Pezhman Jalali, Hamed Osouli Tabrizi, Jae Eun Hyun, Fatemeh Haghayegh, Mahmood Khalghollah, Azam Zare, Byron M Berenger, Yan Dong Niu, Ebrahim Ghafar-Zadeh and 1 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Biosensors & bioelectronics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
–field-weighted citation impact
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

9 citing papers in PubMed.

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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

11 authors.

Razieh SalahandishBioMEMS and Bioinspired Microfluidic Laboratory, Department of Biomedical Engineering, University of Calgary, Calgary, Alberta, T2N 1N4, Canada; Department of Mechanical and Manufacturing Engineering, University of Calgary, University of Calgary, Calgary, Alberta, T2N 1N4, Canada.
Pezhman JalaliBioMEMS and Bioinspired Microfluidic Laboratory, Department of Biomedical Engineering, University of Calgary, Calgary, Alberta, T2N 1N4, Canada.
Hamed Osouli TabriziBiologically Inspired Sensors and Actuators (BioSA), Department of Electrical Engineering and Computer Science, Lassonde School of Engineering, York University, Toronto, M3J1P3, Canada.
Jae Eun HyunDepartment of Ecosystem and Public Health, Faculty of Veterinary Medicine, University of Calgary, Calgary, Alberta, T2N 1N4, Canada.
Fatemeh HaghayeghBioMEMS and Bioinspired Microfluidic Laboratory, Department of Biomedical Engineering, University of Calgary, Calgary, Alberta, T2N 1N4, Canada.
Mahmood KhalghollahBioMEMS and Bioinspired Microfluidic Laboratory, Department of Biomedical Engineering, University of Calgary, Calgary, Alberta, T2N 1N4, Canada; Department of Electrical and Software Engineering, University of Calgary, Calgary, Alberta, T2N 1N4, Canada.
Azam ZareBioMEMS and Bioinspired Microfluidic Laboratory, Department of Biomedical Engineering, University of Calgary, Calgary, Alberta, T2N 1N4, Canada.
Byron M BerengerDepartment of Pathology and Laboratory Medicine, University of Calgary, 3535 Research Rd. Calgary, Alberta, T2L 1Y1, Canada; Alberta Public Health Laboratory, Alberta Precision Laboratories, 3330 Hospital Drive, Calgary, Alberta, T2N 4W4, Canada.
Yan Dong NiuDepartment of Ecosystem and Public Health, Faculty of Veterinary Medicine, University of Calgary, Calgary, Alberta, T2N 1N4, Canada. Electronic address: dongyan.niu@ucalgary.ca.
Ebrahim Ghafar-ZadehBiologically Inspired Sensors and Actuators (BioSA), Department of Electrical Engineering and Computer Science, Lassonde School of Engineering, York University, Toronto, M3J1P3, Canada. Electronic address: egz@cse.yorku.ca.
Amir Sanati-NezhadBioMEMS and Bioinspired Microfluidic Laboratory, Department of Biomedical Engineering, University of Calgary, Calgary, Alberta, T2N 1N4, Canada; Department of Mechanical and Manufacturing Engineering, University of Calgary, University of Calgary, Calgary, Alberta, T2N 1N4, Canada; Biomedical Engineering Graduate Program, University of Calgary, Calgary, Alberta, T2N 1N4, Canada. Electronic address: amir.sanatinezhad@ucalgary.ca.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Electrochemical immuno-biosensors are one of the most promising approaches for accurate, rapid, and quantitative detection of protein biomarkers. The two-working electrode strip is employed for creating a self-supporting system, as a tool for self-validating the acquired results for added reliability. However, the realization of multiplex electrochemical point-of-care testing (ME-POCT) requires advancement in portable, rapid reading, easy-to-use, and low-cost multichannel potentiostat readers. The combined multiplex biosensor strips and multichannel readers allow for suppressing the possible complex matrix effect or ultra-sensitive detection of different protein biomarkers. Herein, a handheld binary-sensing (BiSense) bi-potentiostat was developed to perform electrochemical impedance spectroscopy (EIS)-based signal acquisition from a custom-designed dual-working-electrode immuno-biosensor. BiSense employs a commercially available microcontroller and out-of-shelf components, offering the cheapest yet accurate and reliable time-domain impedance analyzer. A specific electrical board design was developed and customized for impedance signal analysis of SARS-CoV-2 nucleocapsid (N)-protein biosensor in spiked samples and alpha variant clinical nasopharyngeal (NP) swab samples. BiSense showed limit-of-detection (LoD) down to 56 fg/mL for working electrode 1 (WE1) and 68 fg/mL for WE2 and reported with a dynamic detection range of 1 pg/mL to 10 ng/mL for detection of N-protein in spiked samples. The dual biosensing of N-protein in this work was used as a self-validation of the biosensor. The low-cost (∼USD$40) BiSense bi-potentiostat combined with the immuno-biosensors successfully detected COVID-19 infected patients in less than 10 min, with the BiSense reading period shorter than 1.5 min, demonstrating its potential for the realization of ME-POCTs for rapid and hand-held diagnosis of infections.

Indexed as

Biosensing TechniquesCOVID-19Electrochemical TechniquesHumansReproducibility of ResultsSARS-CoV-2Bi-potentiostatElectrochemical biosensingPoint-of-careRapid testsSARS-CoV-2

Identifiers

PMID35728365
PMCPMC9195351

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.