Evidence map›Paper›PMID 36290991›Full record

ArticleBiosensors2022

A Wearable, Textile-Based Polyacrylate Imprinted Electrochemical Sensor for Cortisol Detection in Sweat.

Samuel M Mugo, Weihao Lu, Scott Robertson

Open access · goldAbstract read
In one paragraph

Article in Biosensors, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
3.3field-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

10 citing papers in PubMed, 41 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

3 authors at 1 institution in 1 country.

Samuel M MugoPhysical Sciences Department, MacEwan University, Edmonton, AB T5J4S2, Canada.ORCID 0000-0002-0015-1947
Weihao LuPhysical Sciences Department, MacEwan University, Edmonton, AB T5J4S2, Canada.
Scott RobertsonPhysical Sciences Department, MacEwan University, Edmonton, AB T5J4S2, Canada.
MacEwan University · CA

Funding

Natural Sciences and Engineering Research Council Discovery Grant
6 · The paper itself

Abstract

A wearable, textile-based molecularly imprinted polymer (MIP) electrochemical sensor for cortisol detection in human sweat has been demonstrated. The wearable cortisol sensor was fabricated via layer-by-layer assembly (LbL) on a flexible cotton textile substrate coated with a conductive nanoporous carbon nanotube/cellulose nanocrystal (CNT/CNC) composite suspension, conductive polyaniline (PANI), and a selective cortisol-imprinted poly(glycidylmethacrylate-co-ethylene glycol dimethacrylate) (poly(GMA-co-EGDMA)) decorated with gold nanoparticles (AuNPs), or plated with gold. The cortisol sensor rapidly (<2 min) responded to 9.8−49.5 ng/mL of cortisol, with an average relative standard deviation (%RSD) of 6.4% across the dynamic range, indicating excellent precision. The cortisol sensor yielded an excellent limit of detection (LOD) of 8.00 ng/mL, which is within the typical physiological levels in human sweat. A single cortisol sensor patch could be reused 15 times over a 30-day period with no loss in performance, attesting to excellent reusability. The cortisol sensor patch was successfully verified for use in quantification of cortisol levels in human sweat.

Indexed as

Biosensing TechniquesMetal NanoparticlesMolecular ImprintingNanotubes, CarbonWearable Electronic DevicesCelluloseElectrochemical TechniquesElectrodesGoldHumansHydrocortisoneLimit of DetectionMolecularly Imprinted PolymersSweatTextilesCelluloseGoldHydrocortisoneMolecularly Imprinted PolymersNanotubes, Carboncortisol sensinge-skinsmolecularly imprinted polymers (MIPs)polyacrylatewearable capacitive sensor

Identifiers

PMID36290991
PMCPMC9599184
OpenAlexW4304127648

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.