Evidence map›Paper›PMID 38173614›Full record

ArticleRSC advances2024

Green synthesized gold nanoparticles and CuO-based nonenzymatic sensor for saliva glucose monitoring.

Md Younus Ali, Heman B Abdulrahman, Wei-Ting Ting, Matiar M R Howlader

Open access · goldAbstract read
In one paragraph

Article in RSC advances, 2024. 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
7.7field-weighted citation impact, top 2% 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, 37 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

4 authors at 1 institution in 1 country.

Md Younus AliDepartment of Electrical and Computer Engineering, McMaster University 1280 Main Street West Hamilton ON L8S 4K1 Canada howladm@mcmaster.ca.ORCID https://orcid.org/0000-0002-8239-0975
Heman B AbdulrahmanDepartment of Electrical and Computer Engineering, McMaster University 1280 Main Street West Hamilton ON L8S 4K1 Canada howladm@mcmaster.ca.
Wei-Ting TingDepartment of Electrical and Computer Engineering, McMaster University 1280 Main Street West Hamilton ON L8S 4K1 Canada howladm@mcmaster.ca.
Matiar M R HowladerDepartment of Electrical and Computer Engineering, McMaster University 1280 Main Street West Hamilton ON L8S 4K1 Canada howladm@mcmaster.ca.ORCID https://orcid.org/0000-0001-8423-0791
McMaster University · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Glucose, essential for brain and muscle functions, requires careful monitoring in diabetes and other chronic disease management. While blood glucose monitoring provides precise information about these diseases, it remains an invasive method. Saliva glucose monitoring could offer an alternative approach, but the glucose concentration in saliva is very low. In this work, we report a simple, low-cost, highly sensitive nonenzymatic electrochemical glucose sensor. We developed this sensor using green synthesized gold nanoparticles (AuNPs) and wet chemical synthesized copper oxide (CuO) nanoparticles on a screen-printed carbon electrode (Au/CuO/SPCE). The sensor's high sensitivity results from dual amplification strategies using AuNPs and CuO nanomaterials, each demonstrating catalytic activity towards glucose. This shows promising potential for saliva glucose monitoring. The AuNPs were synthesized using an Au precursor and orange peel extract (OPE), yielding stable colloidal AuNPs with a mean diameter of about 37 nm, thus eliminating the need for additional capping agents. Under optimal conditions, amperometric tests revealed that the sensor responded linearly to glucose concentrations ranging from 2 μM to 397 μM with a sensitivity of 236.70 μA mM

Identifiers

PMID38173614
PMCPMC10758929
OpenAlexW4390508352

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.