Evidence map›Paper›PMID 36097151›Full record

ArticleScientific reports2022

Simple diagnosis of cancer by detecting CEA and CYFRA 21-1 in saliva using electronic sensors.

Sowmya Joshi, Shashidhar Kallappa, Pranjal Kumar, Sudhanshu Shukla, Ruma Ghosh

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed, 36 citations in OpenAlex.

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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

5 authors at 2 institutions in 1 country.

Sowmya JoshiDepartment of Electrical Engineering, Indian Institute of Technology Dharwad, Dharwad, 580011, Karnataka, India.
Shashidhar KallappaDepartment of Surgical Oncology, Karnataka Institute of Medical Sciences, Hubli, 580029, Karnataka, India.
Pranjal KumarDepartment of Biosciences and Bioengineering, Indian Institute of Technology Dharwad, Dharwad, 580011, Karnataka, India.
Sudhanshu ShuklaDepartment of Biosciences and Bioengineering, Indian Institute of Technology Dharwad, Dharwad, 580011, Karnataka, India.
Ruma GhoshDepartment of Electrical Engineering, Indian Institute of Technology Dharwad, Dharwad, 580011, Karnataka, India. rumaghosh@iitdh.ac.in.
Indian Institute of Technology Dharwad · INKarnataka Institute of Medical Sciences · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

One way of early diagnosis of cancer is by detecting the biomarkers that get introduced into easily accessible body fluids. We report the development of portable and rapid electronic biosensors for quantitative detection of two secretive cancer biomarkers-Carcinoembryonic antigen (CEA) and Cytokeratin fragment 19 (CYFRA 21-1). The reduced graphene oxide (rGO)/ melamine (MEL)/antibodies/ bovine serum albumin (BSA) based devices were tested for 1 pg/mL to 800 ng/mL of CEA and CYFRA 21-1. The responses of the sensors ranged from 7.14 to 59.1% and from 6.18 to 64% for 1 pg/mL to 800 ng/mL CEA and CYFRA 21-1 respectively. A read-out circuit was assembled to develop a portable prototype which was used to assess the concentrations of the two antigens present in saliva samples of 14 subjects. The prototype could accurately discriminate between 9 oral squamous cell carcinoma patients and 5 healthy controls.

Indexed as

Carcinoma, Squamous CellLung NeoplasmsMouth NeoplasmsAntigens, NeoplasmCarcinoembryonic AntigenElectronicsHumansKeratin-19Salivaantigen CYFRA21.1Antigens, NeoplasmCarcinoembryonic AntigenKeratin-19

Identifiers

PMID36097151
PMCPMC9468134
OpenAlexW4295249545

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.