Evidence map›Paper›PMID 36291006›Full record

ArticleBiosensors2022

Real-Time Monitoring of Breath Biomarkers with A Magnetoelastic Contactless Gas Sensor: A Proof of Concept.

Alvaro Peña, Juan Diego Aguilera, Daniel Matatagui, Patricia de la Presa, Carmen Horrillo, Antonio Hernando, Pilar Marín

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 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.5field-weighted citation impact, top 20% 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

3 citing papers in PubMed, 18 citations in OpenAlex.

  1. Review
  2. Review
  3. Article
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

7 authors at 3 institutions in 1 country.

Alvaro PeñaInstituto de Magnetismo Aplicado (IMA), Universidad Complutense de Madrid-Administrador de Infraestructuras Ferroviarias (UCM-ADIF), 28230 Las Rozas, Spain.ORCID 0000-0002-9002-8386
Juan Diego AguileraInstituto de Magnetismo Aplicado (IMA), Universidad Complutense de Madrid-Administrador de Infraestructuras Ferroviarias (UCM-ADIF), 28230 Las Rozas, Spain.ORCID 0000-0001-9231-6691
Daniel MatataguiInstituto de Magnetismo Aplicado (IMA), Universidad Complutense de Madrid-Administrador de Infraestructuras Ferroviarias (UCM-ADIF), 28230 Las Rozas, Spain.ORCID 0000-0003-3139-3778
Patricia de la PresaInstituto de Magnetismo Aplicado (IMA), Universidad Complutense de Madrid-Administrador de Infraestructuras Ferroviarias (UCM-ADIF), 28230 Las Rozas, Spain.ORCID 0000-0002-9456-8320
Carmen HorrilloGrupo de Tecnología de Sensores Avanzados (SENSAVAN), Instituto de Tecnologías Físicas y de la Información (ITEFI), Consejo Superior de Investigaciones Científicas (CSIC), 28006 Madrid, Spain.ORCID 0000-0003-2554-3119
Antonio HernandoInstituto de Magnetismo Aplicado (IMA), Universidad Complutense de Madrid-Administrador de Infraestructuras Ferroviarias (UCM-ADIF), 28230 Las Rozas, Spain.ORCID 0000-0002-7307-8859
Pilar MarínInstituto de Magnetismo Aplicado (IMA), Universidad Complutense de Madrid-Administrador de Infraestructuras Ferroviarias (UCM-ADIF), 28230 Las Rozas, Spain.
Universidad Complutense de Madrid · ESConsejo Superior de Investigaciones Científicas · ESMadrid Institute for Advanced Studies · ES

Funding

Comunidad de Madrid S2018/NMT-4321Fundación General CSIC Programa ComfuturoMinisterio de Ciencia e Innovación PRE2019-0875001234Ministerio de Ciencia e Innovación RTI2018-095856-B-C21Ministerio de Ciencia e Innovación RTI2018-095856-B-C22
6 · The paper itself

Abstract

In the quest for effective gas sensors for breath analysis, magnetoelastic resonance-based gas sensors (MEGSs) are remarkable candidates. Thanks to their intrinsic contactless operation, they can be used as non-invasive and portable devices. However, traditional monitoring techniques are bound to slow detection, which hinders their application to fast bio-related reactions. Here we present a method for real-time monitoring of the resonance frequency, with a proof of concept for real-time monitoring of gaseous biomarkers based on resonance frequency. This method was validated with a MEGS based on a Metglass 2826 MB microribbon with a polyvinylpyrrolidone (PVP) nanofiber electrospun functionalization. The device provided a low-noise (RMS = 1.7 Hz), fast (<2 min), and highly reproducible response to humidity (Δf = 46−182 Hz for 17−95% RH), ammonia (Δf = 112 Hz for 40 ppm), and acetone (Δf = 44 Hz for 40 ppm). These analytes are highly important in biomedical applications, particularly ammonia and acetone, which are biomarkers related to diseases such as diabetes. Furthermore, the capability of distinguishing between breath and regular air was demonstrated with real breath measurements. The sensor also exhibited strong resistance to benzene, a common gaseous interferent in breath analysis.

Indexed as

AcetoneAmmoniaBenzeneBiomarkersGasesPovidoneAcetoneAmmoniaBenzeneBiomarkersGasesPovidonebiomarkersbreath analysisdiabetesgas sensorhumiditymagnetoelastic resonancenanofiberpolyvinylpyrrolidoneremote sensingsoft magnets

Identifiers

PMID36291006
PMCPMC9599754
OpenAlexW4306149495

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.